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BSc. Computer Science (CS)

Computer Science Academic Coaching For IT student

BSc. CS is the abbreviation of the Bachelor of Science in Computer Science degree course offered by Mumbai university. This popular course is divided into six semesters spread across 3 years. This course provides students an outlet to explore their interest in computers and Information Technology. Some of the important topics covered in the BSc. CS course are coding, programming languages, computer hardware and software, networking, database management, information technology, mathematics, statistics and electronics.

The colleges in which students enroll for the graduate degree course in BSc. Computer Science might not always impart them in-depth knowledge required to ace those subjects, thereby leaving them woefully underprepared for their exams as well as for a future job. Hrishi Computer Education, one of the best training institutes in Mumbai North (Vasai, Virar, Palghar) region, provides BSc. CS coaching for all subjects across all semesters. Our institute has the good infrastructure facilities and excellent faculty to coach, guide and mentor students pursuing the BSc. CS degree course.

Given below is the Latest Semester-Wise Syllabus for the Course

1stUnit

Unit 1: Computer Abstractions and Technology

Basic structure and operation of a computer, functional units and their interaction. Representation of numbers and characters.

Logic circuits and functions:
Combinational circuits and functions: Basic logic gates and functions, truth tables; logic circuits and functions. Minimization with Karnaugh maps. Synthesis of logic functions with and-or-not gates, nand gates, nor gates. Fan-in and fan-out requirements; tristate buffers. Half adder, full adder, ripple carry adder (Flip flops) Gated S-R and D latches, edge-triggered D latch. Shift registers and registers. Decoders, multiplexers. Sequential circuits and functions: State diagram and state table; finite state machines and their synthesis.

2ndUnit

Unit 2: Instruction set architectures

Instruction set architectures:
Basic structure and operation of a computer, functional units and their interaction. Representation of numbers and characters.

Logic circuits and functions:
Memory organization, addressing and operations; word size, big-endian and little-endian arrangements. Instructions, sequencing. Instruction sets for RISC and CISC (examples Altera NIOS II and Freescale ColdFire). Operand addressing modes; pointers; indexing for arrays. Machine language, assembly language, assembler directives. Function calls, processor runtime stack, stack frame. Types of machine instructions: arithmetic, logic, shift, etc. Instruction sets, RISC and CISC examples.

3rdUnit

Unit 3: Basic Processor Unit:

Main components of a processor: registers and register files, ALU, control unit, instruction fetch unit, interfaces to instruction and data memories. Datapath. Instruction fetch and execute; executing arithmetic/logic, memory access and branch instructions; hardwired and micro programmed control for RISC and CISC.

Basic I/O:
Accessing I/O devices, data transfers between processor and I/O devices. Interrupts and exceptions: interrupt requests and processing.

1stUnit

Reasons for Python as the learner’s first programming language, Expression evaluation

Reasons for Python as the learner’s first programming language. Introduction to the IDLE interpreter (shell) and its documentation. Expression evaluation: similarities and differences compared to a calculator; expressions and operators of types int, float, boolean. Built-in function type. Operator precedence. Enumeration of simple and compound statements. The expression statement. The assert statement, whose operand is a boolean expression (values true or false). The assignment statement, dynamic binding of names to values, (type is associated with data and not with names); automatic and implicit declaration of variable names with the assignment statement; assigning the valueNone to a name. The del (delete) statement. Input/output with print and input functions. A statement list (semicolon-separated list of simple statements on a single line) as a single interpreter command. The import statement for already-defined functions and constants. The augmented assignment statement. The built-in help() function. Interactive and script modes of IDLE, running a script, restarting the shell. The compound statement def to define functions; the role of indentation for delimiting the body of a compound statement; calling a previously defined function. Compound data types str, tuple and list (enclosed in quotes, parentheses and brackets, respectively). Indexing individual elements within these types. Strings and tuples are immutable, lists are mutable. Built-in functions min, max, sum. Interactive solution of model problems, (e.g., finding the square root of a number or zero of a function), by repeatedly executing the body of a loop (where the body is a statement list).

2ndUnit

Unit 2: Functions, conditional statements, Dictionaries

Advantages of functions, function parameters, formal parameters, actual parameters, global and local variables. The range function, the iterative for statement. The conditional statements if, if-else, if-else-else. The iterative statements while, while-else, for-else. The continue statement to skip over one iteration of a loop, the break statement to exit the loop. Nested compound statements. Dictionaries: concept of key-value pairs, techniques to create, update and delete dictionary items. Problem-solving using compound types and statements.

3rdUnit

Unit 3: Anonymous functions. List comprehensions.

Anonymous functions. List comprehensions. Gentle introduction to object-oriented programming; using the built-in dir() function, enumerate the methods of strings, tuples, lists, dictionaries. Using these methods for problem-solving with compound types.

1stUnit

Unit 1: Introduction, Methodologies, Social Impact:

Introduction:
Open Source, Free Software, Free Software vs. Open Source software, Public Domain Software, FOSS does not mean no cost. History: BSD, The Free Software Foundation and the GNU Project.

Methodologies:
Open Source History, Initiatives, Principle and methodologies. Philosophy : Software Freedom, Open Source Development Model Licenses and Patents: What Is A License, Important FOSS Licenses (Apache,BSD,GPL, LGPL), copyrights and copy lefts, Patents Economics of FOSS : Zero Marginal Cost, Income-generation opportunities, Problems with traditional commercial software, Internationalization.

Social Impact:
Open source vs. closed source, Open source government, Open source ethics. Social and Financial impacts of open source technology, Shared software, Shared source, Open Source in Government.

2ndUnit

Unit 2: Case Studies, Contributing to Open Source Projects

Example Projects:
Apache web server, GNU/Linux, Android, Mozilla (Firefox), Wikipedia, Drupal, wordpress, GCC, GDB, github, Open Office. Study: Understanding the developmental models, licensings, mode of funding, commercial/non-commercial use. Open Source Hardware, Open Source Design, Open source Teaching. Open source media. Collaboration, Community and Communication

Contributing to Open Source Projects:
Introduction to github, interacting with the community on github, Communication and etiquette, testing open source code, reporting issues, contributing code. Introduction to wikipedia, contributing to Wikipedia Or contributing to any prominent open source project of student’s choice. Starting and Maintaining own Open Source Project.

3rdUnit

Unit 3: Understanding Open Source Ecosystem

Open Source Operating Systems: GNU/Linux, Android, Free BSD, Open Solaris. Open Source Hardware, Virtualization Technologies, Containerization Technologies: Docker, Development tools, IDEs, debuggers, Programming languages, LAMP, Open Source database technologies

1stUnit

Unit 1: Introduction to DBMS

Database, DBMS – Definition, Overview of DBMS, Advantages of DBMS, Levels of abstraction, Data independence, DBMS Architecture.

Data models:
Client/Server Architecture, Object Based Logical Model, Record Based Logical Model (relational, hierarchical, network).

Entity Relationship Model:
Entities, attributes, entity sets, relations, relationship sets, Additional constraints ( key constraints, participation constraints, weak entities, aggregation / generalization, Conceptual Design using ER ( entities VS attributes, Entity Vs relationship, binary Vs ternary, constraints beyond ER)

Relational data model:
Domains, attributes, Tuples and Relations, Relational Model Notation, Characteristics of Relations, Relational Constraints - primary key, referential integrity, unique constraint, Null constraint, Check constraint.

ER to Table:
Entity to Table, Relationship to tables with and without key constraints

2ndUnit

Unit 2: Schema refinement and Normal forms

Functional dependencies, first, second, third, and BCNF normal forms based on primary keys, lossless join decomposition.

Relational Algebra:
Operations (selection, projection, set operations union, intersection, difference, cross product, Joins –conditional, equi join and natural joins, division).

DDL Statements:
Creating Databases, Using Databases, datatypes, Creating Tables (with integrity constraints – primary key, default, check, not null), Altering Tables, Renaming Tables, Dropping Tables, Truncating Tables, Backing Up and Restoring databases.

DML Statements:
Viewing the structure of a table insert, update, delete, Select all columns, specific columns, unique records, conditional select, in clause, between clause, limit, aggregate functions (count, min, max, avg, sum), group by clause, having clause.

3rdUnit

Unit 3: Functions

String Functions (concat, instr, left, right, mid, length, lcase/lower, ucase/upper, replace, strcmp, trim, ltrim, rtrim), Math Functions (abs, ceil, floor, mod, pow, sqrt, round, truncate) Date Functions (adddate, datediff, day, month, year, hour, min, sec, now, reverse).

Joining Tables:
Inner join, outer join (left outer, right outer, full outer).

Sub-queries:
Subqueries with IN, EXISTS, subqueries restrictions, Nested subqueries, ANY/ALL clause, correlated subqueries.

Database Protection:
Security Issues, Threats to Databases, Security Mechanisms, Role of DBA, Discretionary Access Control.

Views:
(Creating, Altering Dropping, Renaming and Manipulating views).

DCL Statements:
(Creating/dropping users, privileges introduction, granting/revoking privileges, viewing privileges)

1stUnit

Unit 1: Recurrence Relations

Functions:
Definition of function. Domain, co domain and the range of a function. Direct and inverse images. Injective, surjective and bijective functions. Composite and inverse functions.

Relations:
Definition and examples. Properties of relations , Partial Ordering sets, Linear Ordering Hasse Daigrams , Maximum and Minimum elements, Lattices.

Recurrence Relations:
Definition of recurrence relations, Formulating recurrence relations, solving recurrence relations- Back tracking method, Linear homogeneous recurrence relations with constant coefficients. Solving linear homogeneous recurrence relations with constant coefficients of degree two when characteristic equation has distinct roots and only one root, Particular solutions of non linear homogeneous recurrence relation, Solution of recurrence relation by the method of generation functions, Applications- Formulate and solve recurrence relation for Fibonacci numbers, Tower of Hanoi, Intersection of lines in a plane, Sorting Algorithms.

2ndUnit

Unit 2: Counting Principles, Languages and Finite State Machine

Permutations and Combinations:
Partition and Distribution of objects, Permutation with distinct and indistinct objects, Binomial numbers, Combination with identities: Pascal Identity, Vandermonde’s Identity, Pascal triangle, Binomial theorem, Combination with indistinct objects.

Counting Principles:
Creating Databases, Using Databases, datatypes, Creating Tables (with integrity constraints – primary key, default, check, not null), Altering Tables, Renaming Tables, Dropping Tables, Truncating Tables, Backing Up and Restoring databases.

Languages, Grammars and Machines:
Languages , regular Expression and Regular languages, Finite state Automata, grammars, Finite state machines, Gödel numbers, Turing machines.

3rdUnit

Unit 3: Graphs and Trees

Graphs:
Definition and elementary results, Adjacency matrix, path matrix, Representing relations using diagraphs, Warshall’s algorithm- shortest path , Linked representation of a graph, Operations on graph with algorithms - searching in a graph; Insertion in a graph, Deleting from a graph, Traversing a graph Breadth-First search and Depth-First search.

Trees:
Definition and elementary results. Ordered rooted tree, Binary trees, Complete and extended binary trees, representing binary trees in memory, traversing binary trees, binary search tree, Algorithms for searching and inserting in binary search trees, Algorithms for deleting in a binary search tree.

1stUnit

Unit 1: Data Presentation, Data Aggregation

Data Types:
Attribute, variable, discrete and continuous variable Data presentation : frequency distribution, histogram o give, curves, stem and leaf display.

Data Aggregation:
Measures of Central tendency: Mean, Median, mode for raw data, discrete, grouped frequency distribution. Measures dispersion: Variance, standard deviation, coefficient of variation for raw data, discrete and grouped frequency distribution, quartiles, quantiles Real life examples.

Entity Relationship Model:
Entities, attributes, entity sets, relations, relationship sets, Additional constraints ( key constraints, participation constraints, weak entities, aggregation / generalization, Conceptual Design using ER ( entities VS attributes, Entity Vs relationship, binary Vs ternary, constraints beyond ER)

2ndUnit

Unit 2: Moments

Raw moments, central moments, relation between raw and central moments.

Measures of Skewness and Kurtosis:
Operations (selection, projection, set operations union, intersection, difference, cross product, Joins –conditional, equi join and natural joins, division).

DDL Statements:
Based on moments, quartiles, relation between mean, median, Mode for symmetric, asymmetric frequency curve.

Correlation and Regression:
Bivariate data, scatter plot, correlation, nonsense correlation, Karl Pearson’s coefficients of correlation,independence.

Linear regression:
Fitting of linear regression using least square regression, coefficient of determination, properties of regression coefficients (only statement).

3rdUnit

Unit 3: Probability

Random experiment, sample space, events types and operations of events Probability definition : classical, axiomatic, Elementary Theorems of probability (without proof)
- 0 ≤ P(A) ≤ 1,
-P(A U B) = P(A) + P(B)
- P(A U B) - P (A’) = 1
- P(A) - P(A) ≤ P(B)
if A C B Conditional probability, ‘Bayes’ theorem, independence, Examples on Probability

1stUnit

Unit 1: Introduction to Soft Skills and Hard Skills

Personality Development:
Knowing Yourself, Positive Thinking, Johari’s Window, Communication Skills, Non-verbal Communication, Physical Fitness.

Emotional Intelligence:
Meaning and Definition, Need for Emotional Intelligence, Intelligence Quotient versus Emotional Intelligence Quotient, Components of Emotional Intelligence, Competencies of Emotional Intelligence, Skills to Develop Emotional Intelligence.

Etiquette and Mannerism:
Introduction, Professional Etiquette, Technology Etiquette

Communication Today:
Significance of Communication, GSC’s 3M Model of Communication, Vitality of the Communication Process, Virtues of Listening, Fundamentals of Good Listening, Nature of Non-Verbal Communication, Need for Intercultural Communication, Communicating Digital World.

2ndUnit

Unit 2: Academic Skills

Employment Communication:
Introduction, Resume, Curriculum Vitae, Scannable Resume, Developing an Impressive Resume, Formats of Resume, Job Application or Cover Letter.

Professional Presentation:
Nature of Oral Presentation, Planning a Presentation, Preparing the Presentation, Delivering the Presentation.

Job Interviews:
Introduction, Importance of Resume, Definition of Interview, Background Information, Types of Interviews, Preparatory Steps for Job Interviews, Interview Skill Tips, Changes in the Interview Process, FAQ During Interviews.

Group Discussion:
Introduction, Ambience/Seating Arrangement for Group Discussion, Importance of Group Discussions, Difference between Group Discussion, Panel Discussion and Debate, Traits, Types of Group Discussions, topic based and Case based Group Discussion, Individual Traits

3rdUnit

Unit 3: Professional Skills

JCreativity at Workplace:
Introduction, Current Workplaces, Creativity, Motivation, Nurturing Hobbies at Work, The Six Thinking Hat Method.

Capacity Building:
Learn, Unlearn and Relearn: Capacity Building, Elements of Capacity Building, Zones of Learning, Ideas for Learning, Strategies for Capacity Building.

Leadership and Team Building:
Leader and Leadership, Leadership Traits, Culture and Leadership, Leadership Styles and Trends, Team Building, Types of Teams.

Decision Making and Negotiation:
Security Issues, Threats to Databases, Security Mechanisms, Role of DBA, Discretionary Access Control.

Views:
Introduction to Decision Making, Steps for Decision Making, Decision Making Techniques, Negotiation Fundamentals, Negotiation Styles, Major Negotiation Concepts.

Stress and Time Management:
Stress, Sources of Stress, Ways to Cope with Stress.

1stUnit

Unit 1: Structure of C program

Structure of C program:
Header and body, Use of comments. Interpreters vs compilers, Python vs C. Compilation of a program. Formatted I/O: printf(), scanf().

Data:
Variables, Constants, data types like: int, float char, double and void, short and long size qualifiers, signed and unsigned qualifiers. Compare with datatypes in Python. Compare static typing in C vs dynamic typing in Python.

Variables:
Declaring variables, scope of the variables according to block, hierarchy of data types. Compare explicit declarations in C with implicit declarations in Python.

Types of operators:
Arithmetic, relational, logical, compound assignment, increment and decrement, conditional or ternary, bitwise and comma operators. Precedence and order of evaluation, statements and Expressions. Automatic and explicit type conversion.

Iterations:
Control statements for decision making: (i) Branching: if statement, else.. if statement, (does the writer mean if-else or nested ifs)switch statement. (ii) Looping: while loop, do.. while, for loop. (iii) Jump statements: break, continue and goto.

2ndUnit

Unit 2: Arrays

(One and two dimensional), declaring array variables, initialization of arrays, accessing array elements. Compare array types of C with list and tuple types of Python.

Data Input and Output functions:
Character I/O format: getch(), getche(), getchar(), getc(), gets(), putchar(), putc(), puts().

Manipulating Strings:
Declaring and initializing String variables, Character and string handling functions. Compare with Python strings.

Functions:
Function declaration, function definition, Global and local variables, return statement, Calling a function by passing values.

Recursion:
Definition, Recursive functions.

3rdUnit

Unit 3: Pointer

Fundamentals, Pointer variables, Referencing and de-referencing, Pointer Arithmetic, Using Pointers with Arrays, Using Pointers with Strings, Array of Pointers, Pointers as function arguments, Functions returning pointers.

Dynamic Memory Allocation:
malloc(), calloc(), realloc(), free() and sizeof operator. Compare with automatic garbage collection in Python.

Structure:
Declaration of structure, reading and assignment of structure variables, Array of structures, arrays within structures, structures within structures. Compare C structures with Python tuples.

Unions:
Defining and working with unions. File handling: Different types of files like text and binary.

Different types of functions:
fopen(), fclose(), fgetc(), fputc(), fgets(), fputs(), fscanf(), fprintf(), getw(), putw(), fread(), fwrite(), fseek().

1stUnit

Unit 1: Python File Input-Output

Opening and closing files, various types of file modes, reading and writing to files, manipulating directories. Iterables, iterators and their problem solving applications.

Exception handling:
What is an exception, various keywords to handle exceptions such try, catch, except, else, finally, raise.

Regular Expressions:
Concept of regular expression, various types of regular expressions, using match function.

2ndUnit

Unit 2: GUI Programming in Python (using Tkinter/wxPython/Qt)

What is GUI, Advantages of GUI, Introduction to GUI library. Layout management, events and bindings, fonts, colours, drawing on canvas (line, oval, rectangle, etc.) Widgets such as : frame, label, button, checkbutton, entry, listbox, message, radiobutton, text, spinbox etc

3rdUnit

Unit 3: Database connectivity in Python

Installing mysql connector, accessing connector module module, using connect, cursor, execute & close functions, reading single & multiple results of query execution, executing different types of statements, executing transactions, understanding exceptions in database connectivity.

Network connectivity:
Socket module, creating server-client programs, sending email, reading from URL

1stUnit

Unit 1: Introduction, Installation, Linux Structure

History of Linux, Philosophy, Community, Terminology, Distributions, Linux kernel vs distribution. Why learn Linux? Importance of Linux in software ecosystem: web servers, supercomputers, mobile, servers.

Installation:
Installation methods, Hands on Installation using CD/DVD or USB drive.

Linux Structure:
Linux Architecture, File system basics, The boot process, init scripts, run Levels, shutdown process, Very basic introductions to Linux processes, Packaging methods: rpm/deb, Graphical Vs Command line.

2ndUnit

Unit 2: Graphical Desktop

Session Management, Basic Desktop Operations, Network Management, Installing and Updating Software, Text editors: gedit, vi, vim, emacs, Graphics editors, Multimedia applications.

Command Line:
Command line mode options, Shells, Basic Commands, General Purpose Utilities, Installing Software, User management, Environment variables, Command aliases.

Linux Documentation:
man pages, GNU info, help command, More documentation sources.

File Operations:
Filesystem, Filesystem architecture, File types, File attributes, Working with files, Backup, compression.

1stUnit

Unit 1: Abstract Data Types

Introduction, The Date Abstract Data Type, Bags, Iterators. Application

Arrays:
Array Structure, Python List, Two Dimensional Arrays, Matrix Abstract Data Type, Application.

Sets and Maps:
Sets-Set ADT, Selecting Data Structure, List based Implementation, Maps-Map ADT, List Based Implementation, Multi-Dimensional Arrays-Multi-Array ADT, Implementing Multiarrays, Application.

Algorithm Analysis:
Complexity Analysis-Big-O Notation, Evaluating Python Code, Evaluating Python List, Amortized Cost, Evaluating Set ADT, Application.

Searching and Sorting:
Searching-Linear Search, Binary Search, Sorting-Bubble, Selection and Insertion Sort, Working with Sorted Lists-Maintaining Sorted List, Maintaining sorted Lists.

2ndUnit

Unit 2: Linked Structures

Introduction, Singly Linked List-Traversing, Searching, Prepending and Removing Nodes, Bag ADT-Linked List Implementation. Comparing Implementations, Linked List Iterators, More Ways to Build Kinked Lists, Applications-Polynomials Stacks: Stack ADT, Implementing

Stacks:
Using Python List, Using Linked List, Stack Applications-Balanced Delimiters, Evaluating Postfix Expressions.

Queues:
Queue ADT, Implementing Queue-Using Python List, Circular Array, Using List, Priority Queues- Priority Queue ADT, Bounded and unbounded Priority Queues.

Advanced Linked List:
Doubly Linked Lists-Organization and Operation, Circular Linked List-Organization and Operation, Multi Lists.

3rdUnit

Unit 3: Recursion

Recursive Functions, Properties of Recursion, Its working, Recursive Applications.

Hash Table:
Introduction, Hashing-Linear Probing, Clustering, Rehashing, Separate Chaining, Hash Functions.

Advanced Sorting:
Merge Sort, Quick Sort, Radix Sort, Sorting Linked List.

Binary Trees:
Tree Structure, Binary Tree-Properties, Implementation and Traversals, Expression Trees, Heaps and Heap sort, Search Trees.

1stUnit

Unit 1: Derivatives and its Applications

Review of Functions, limit of a function, continuity of a function, derivative function. Derivative In Graphing And Applications: Analysis of Functions: Increase, Decrease, Concavity, Relative Extrema; Graphing Polynomials, Rational Functions, Cusps and Vertical Tangents. Absolute Maxima and Minima, Applied Maximum and Minimum Problems, Newton’s Method.

2ndUnit

Unit 2: INTEGRATION AND ITS APPLICATIONS

An Overview of the Area Problem, Indefinite Integral, Definition of Area as a Limit; Sigma Notation, Definite Integral, Evaluating Definite Integrals by Substitution, Area Between Two Curves, Length of a Plane Curve. Numerical Integration: Simpson’s Rule. Modeling with Differential Equations, Separation of Variables, Slope Fields, Euler’s Method, FirstOrder Differential Equations and Applications.

3rdUnit

Unit 3: PARTIAL DERIVATIVES AND ITS APPLICATIONS:

Functions of Two or More Variables Limits and Continuity Partial Derivatives, Differentiability, Differentials, and Local Linearity, Chain Rule, Directional Derivatives and Gradients, Tangent Planes and Normal, Vectors, Maxima and Minima of Functions of Two Variables.

1stUnit

Unit 1: Standard distributions

Standard distributions: random variable; discrete, continuous, expectation and variance of a random variable, pmf, pdf, cdf, reliability, Introduction and properties without proof for following distributions; binomial, normal, chi-square, t, F. Examples

2ndUnit

Unit 2: Hypothesis testing

one sided, two sided hypothesis, critical region, p-value, tests based on t, Normal and F, confidence intervals. Analysis of variance : one-way, two-way analysis of variance

3rdUnit

Unit 3: Non-parametric tests

Need of non-parametric tests, sign test, Wilicoxon’s signed rank test, run test, Kruskal-Walis tests. Post-hoc analysis of one-way analysis of variance : Duncan’s test Chi-square test of association

1stUnit

Unit 1: Green IT Overview, Green Devices and Hardware, Green Software, Sustainable Software Development

Introduction , Environmental Concerns and Sustainable Development, Environmental Impacts of IT, Green I , Holistic Approach to Greening IT, Greening IT, Applying IT for Enhancing Environmental Sustainability, Green IT Standards and Eco-Labelling of IT , Enterprise Green IT Strategy, Green Washing, Green IT: Burden or Opportunity?

Green Devices and Hardware: Introduction, Life Cycle of a Device or Hardware, Reuse, Recycle and Dispose

Green Software: Introduction, Processor Power States , Energy-Saving Software Techniques, Evaluating and Measuring Software Impact to Platform Power

Sustainable Software Development: Introduction, Current Practices, Sustainable Software, Software Sustainability Attributes, Software Sustainability Metrics, Sustainable Software Methodology, Defining Actions

2ndUnit

Unit 2: Green Data Centres, Green Data Storage, Green Networks and Communications, Enterprise Green IT Strategy

Data Centres and Associated Energy Challenges, Data Centre IT Infrastructure, Data Centre Facility Infrastructure: Implications for Energy Efficiency, IT Infrastructure Management, Green Data Centre Metrics.

Green Data Storage:
Introduction,Storage Media Power Characteristics, Energy Management Techniques for Hard Disks, System-Level Energy Management

Green Networks and Communications:
Introduction, Objectives of Green Network Protocols, Green Network Protocols and Standards

Enterprise Green IT Strategy:
Introduction, Approaching Green IT Strategies, Business Drivers of Green IT Strategy, Business Dimensions for Green IT Transformation, Organizational Considerations in a Green IT Strategy, Steps in Developing a Green IT Strategy, Metrics and Measurements in Green Strategies.

3rdUnit

Unit 3: Sustainable Information Systems and Green Metrics, Enterprise Green IT Readiness, Sustainable IT Services, Green Enterprises and the role of IT

Introduction, Multilevel Sustainable Information, Sustainability Hierarchy Models, Product Level Information, Individual Level Information, Functional Level Information, Organizational Level Information, Measuring the Maturity of Sustainable ICT

Enterprise Green IT Readiness:
Introduction, Readiness and Capability, Development of the G-Readiness Framework, Measuring an Organization's G-Readiness

Sustainable IT Services:
Creating a Framework for Service Innovation: Introduction, Factors Driving the Development of Sustainable IT, Sustainable IT Services (SITS), SITS Strategic Framework.

Green Enterprises and the Role of IT:
Introduction, Organizational and Enterprise Greening, Information Systems in Greening Enterprises, Greening the Enterprise: IT Usage and Hardware, Inter-organizational Enterprise Activities and Green Issues.

1stUnit

Unit 1: Automata Theory

Defining Automaton, Finite Automaton, Transitios and Its properties, Acceptability by Finite Automaton, Nondeterministic Finite State Machines, DFA and NDFA equivalence, Mealy and Moore Machines, Minimizing Automata.

Formal Languges:
Defining Grammar, Derivations, Languges generated by Grammar, Comsky Classification of Grammar and Languages, Recursive Enumerable Sets, Operations on Languages, Languages and Automata

2ndUnit

Unit 2: Regular Sets and Regular Grammar, Context Free Languages

Regular Sets and Regular Grammar:
Regular Grammar, Regular Expressions, Finite automata and Regular Expressions, Pumping Lemma and its Applications, Closure Properties, Regular Sets and Regular Grammar.

Context Free Languages:
Context-free Languages, Derivation Tree, Ambiguity of Grammar, CFG simplification, Normal Forms, Pumping Lemma for CFG Pushdown Automata: Definitions, Acceptance by PDA, PDA and CFG.

3rdUnit

Unit 3: Linear Bound Automata, Turing Machines, Undecidability

Linear Bound Automata:
The Linear Bound Automata Model, Linear Bound Automata and Languages.

Turing Machines:
Turing Machine Definition, Representations, Acceptability by Turing Machines, Designing and Description of Turing Machines, Turing Machine Construction, Variants of Turing Machine.

Undecidability:
The Church-Turing thesis, Universal Turing Machine, Halting Problem, Introduction to Unsolvable Problems.

1stUnit

Unit 1: The Java Language, OOPS, String Manipulations

Introduction:
Features of Java, Java programming format, Java Tokens, Java Statements, Java Data Types, Typecasting, Arrays

OOPS:
Introduction, Class, Object, Static Keywords, Constructors, this Key Word, Inheritance, super Key Word, Polymorphism (overloading and overriding), Abstraction, Encapsulation, Abstract Classes, Interfaces

String Manipulations:
String, String Buffer, String Tokenizer Packages: Introduction to predefined packages (java.lang, java.util, java.io, java.sql, java.swing), User Defined Packages, Access specifiers

2ndUnit

Unit 2: Exception Handling, Multithreading

Exception Handling:
Introduction, Pre-Defined Exceptions, Try-Catch-Finally, Throws, throw, User Defined Exception examples

Multithreading:
Thread Creations, Thread Life Cycle, Life Cycle Methods, Synchronization, Wait() notify() notify all() methods.

I/O Streams:
Introduction, Byte-oriented streams, Character- oriented streams, File, Random access File, Serialization Networking: Introduction, Socket, Server socket, Client –Server Communication

3rdUnit

Unit 3: Wrapper Classes, Inner Classes, AWT

Wrapper Classes:
Introduction, Operations on the Stack Memory Representation of Stack, Array Representation of Stack, Applications of Stack, Evaluation of Arithmetic Expression, Matching Parenthesis, infix and postfix operations, Recursion.

Inner Classes:
Introduction, Member inner class, Static inner class, Local inner class, Anonymous inner class

AWT:
Introduction, Components, Event-Delegation-Model, Listeners, Layouts, Individual components Label, Button, CheckBox, Radio Button, Choice, List, Menu, Text Field, Text Area.

1stUnit

Unit 1: Introduction and Operating-Systems Structures

Definition of Operating system, Operating System’s role, Operating-System Operations, Functions of Operating System, Computing Environments

Operating-System Structures:
Operating-System Services, User and Operating-System Interface, System Calls, Types of System Calls, Operating-System Structure

Processes:
Process Concept, Process Scheduling, Operations on Processes, Interprocess Communication

Threads:
Overview, Multicore Programming, Multithreading Models.

2ndUnit

Unit 2: Process Synchronization

General structure of a typical process, race condition, The Critical-Section Problem, Peterson’s Solution, Synchronization Hardware, Mutex Locks, Semaphores, Classic Problems of Synchronization, Monitors.

CPU Scheduling:
Basic Concepts, Scheduling Criteria, Scheduling Algorithms (FCFS, SJF, SRTF, Priority, RR, Multilevel Queue Scheduling, Multilevel Feedback Queue Scheduling), Thread Scheduling.

Deadlocks:
System Model, Deadlock Characterization, Methods for Handling Deadlocks, Deadlock Prevention, Deadlock Avoidance, Deadlock Detection, Recovery from Deadlock

3rdUnit

Unit 3: Main Memory

Background, Logical address space, Physical address space, MMU, Swapping, Contiguous Memory Allocation, Segmentation, Paging, Structure of the Page Table.

Virtual Memory:
Background, Demand Paging, Copy-on-Write, Page Replacement, Allocation of Frames, Thrashing.

Mass-Storage Structure:
Overview, Disk Structure, Disk Scheduling, Disk Management.

File-System Interface:
File Concept, Access Methods, Directory and Disk Structure, File-System Mounting, File Sharing.

File-System Implementation:
File-System Structure, File-System Implementation, Directory Implementation, Allocation Methods, Free-Space Management.

1stUnit

Unit 1: Stored Procedures

Stored Procedures:
Types and benefits of stored procedures, creating stored procedures, executing stored procedures, altering stored procedures, viewing stored procedures.

Triggers:
Concept of triggers, Implementing triggers – creating triggers, Insert, delete, and update triggers, nested triggers, viewing, deleting and modifying triggers, and enforcing data integrity through triggers.

Sequences:
Creating sequences, referencing, altering and dropping a sequence.

File Organization and Indexing:
Cluster, Primary and secondary indexing, Index data structure: hash and Tree based indexing, Comparison of file organization: cost model, Heap files, sorted files, clustered files. Creating, dropping and maintaining indexes.

Fundamentals of PL/SQL:
Defining variables and constants, PL/SQL expressions and comparisons: Logical Operators, Boolean Expressions, CASE Expressions Handling, Null Values in Comparisons and Conditional Statements, PL/SQL Datatypes: Number Types, Character Types, Boolean Type, Datetime and Interval Types.

2ndUnit

Unit 2: Overview of PL/SQL Control Structures

Overview of PL/SQL Control Structures:
Conditional Control: IF and CASE Statements, IF-THEN Statement, IF-THEN-ELSE Statement, IFTHEN-ELSIF Statement, CASE Statement, Iterative Control: LOOP and EXIT Statements, WHILE-LOOP, FOR-LOOP, Sequential Control: GOTO and NULL Statements.

3rdUnit

Unit 3: Transaction Management

Transaction Management:
ACID Properties, Serializability, Two-phase Commit Protocol, Concurrency Control, Lock Management, Lost Update Problem, Inconsistent Read Problem , Read-Write Locks, Deadlocks Handling, Two Phase Locking protocol.

DCL Statements:
Defining a transaction, Making Changes Permanent with COMMIT, Undoing Changes with ROLLBACK, Undoing Partial Changes with SAVEPOINT and ROLLBACK

Crash Recovery:
ARIES algorithm. The log based recovery, recovery related structures like transaction and dirty page table, Write-ahead log protocol, check points, recovery from a system crash, Redo and Undo phases.

1stUnit

Unit 1: Introduction to Combinatorics

Introduction to Combinatorics:
Enumeration, Combinatorics and Graph Theory/ Number Theory/Geometry and Optimization, Sudoku Puzzles.

Strings, Sets, and Binomial Coefficients:
Strings- A First Look, Combinations, Combinatorial, the Ubiquitous Nature of Binomial Coefficients, The Binomial, Multinomial Coefficients.

Induction:
Introduction, The Positive Integers are Well Ordered, The Meaning of Statements, Binomial Coefficients Revisited, Solving Combinatorial Problems Recursively, Mathematical Induction, and Inductive Definitions Proofs by Induction. Strong Induction

2ndUnit

Unit 2: Graph Theory

Graph Theory:
Basic Notation and Terminology, Multigraphs: Loops and Multiple Edges, Eulerian and Hamiltonian Graphs, Graph Coloring, Planar Counting, Labeled Trees, A Digression into Complexity Theory. Applying Probability to Combinatorics, Small Ramsey Numbers, Estimating Ramsey Numbers, Applying Probability to Ramsey Theory, Ramsey’s Theorem The Probabilistic Method.

3rdUnit

Unit 3: Network Flows

Network Flows:
Basic Notation and Terminology, Flows and Cuts, Augmenting Paths, The Ford-Fulkerson Labeling Algorithm A Concrete Example, Integer Solutions of Linear Programming Problems. Combinatorial Applications of Network Flows: Introduction, Matching in Bipartite Graphs, Chain partitioning, Pólya’s Enumeration Theorem: Coloring the Vertices of a Square.

1stUnit

Unit 1: SoC and Raspberry Pi

SoC and Raspberry Pi:
System on Chip: What is System on chip? Structure of System on Chip.

SoC products:
FPGA, GPU, APU, Compute Units

ARM 8 Architecture:
SoC on ARM 8. ARM 8 Architecture Introduction.

Introduction to Raspberry Pi:
Introduction to Raspberry Pi, Raspberry Pi Hardware, Preparing your raspberry Pi.

Raspberry Pi Boot:
Learn how this small SoC boots without BIOS. Configuring boot sequences and hardware.

2ndUnit

Unit 2: Programming Raspberry Pi

Raspberry Pi and Linux :
About Raspbian, Linux Commands, Configuring Raspberry Pi with Linux Commands Programing interfaces: Introduction to Node.js, Python.

Raspberry Pi Interfaces:
UART, GPIO, I2C, SPI

Useful Implementations:
Cross Compilation, Pulse Width Modulation, SPI for Camera.

3rdUnit

Unit 3: Introduction to IoT

What is IoT? IoT examples, Simple IoT LED Program:
IoT and Protocols

IoT Security:
HTTP, UPnp, CoAP, MQTT, XMPP.

IoT Service as a Platform:
Clayster, Thinger.io, SenseIoT, carriots and Node RED.

IoT Security and Interoperability:
Risks, Modes of Attacks, Tools for Security and Interoperability.

1stUnit

Unit 1: HTML5

HTML5:
Fundamental Elements of HTML, Formatting Text in HTML, Organizing Text in HTML, Links and URLs in HTML, Tables in HTML, Images on a Web Page, Image Formats, Image Maps, Colors, FORMs in HTML, Interactive Elements, Working with Multimedia - Audio and Video File Formats, HTML elements for inserting Audio / Video on a web page
CSS: Understanding the Syntax of CSS, CSS Selectors, Inserting CSS in an HTML Document, CSS properties to work with background of a Page, CSS properties to work with Fonts and Text Styles, CSS properties for positioning an element.

2ndUnit

Unit 2: JavaScript, XML

JavaScript:
Using JavaScript in an HTML Document, Programming Fundamentals of JavaScript – Variables, Operators, Control Flow Statements, Popup Boxes, Functions – Defining and Invoking a Function, Defining Function arguments, Defining a Return Statement, Calling Functions with Timer, JavaScript Objects - String, RegExp, Math, Date, Browser Objects - Window, Navigator, History, Location, Document, Cookies, Document Object Model, Form Validation using JavaScript.

XML:
Comparing XML with HTML, Advantages and Disadvantages of XML, Structure of an XML Document, XML Entity References, DTD, XSLT: XSLT Elements and Attributes - xsl:template, xsl:apply-templates, xsl:import, xsl:call-template, xsl:include, xsl:element, xsl:attribute, e xsl:attribute-set, xsl:value-of.

3rdUnit

Unit 3: AJAX

AJAX:
AJAX Web Application Model, How AJAX Works, XMLHttpRequest Object – Properties and Methods, Handling asynchronous requests using AJAX.

PHP:
Variables and Operators, Program Flow, Arrays, Working with Files and Directories, Working with Databases, Working with Cookies, Sessions and Headers.

Introduction to jQuery:
Fundamentals, Selectors, methods to access HTML attributes, methods for traversing, manipulators, events, effects.

1stUnit

Unit 1: Introduction to algorithm

Introduction to algorithm:
Why to analysis algorithm, Running time analysis, How to Compare Algorithms, Rate of Growth, Commonly Used Rates of Growth, Types of Analysis, Asymptotic Notation, Big-O Notation, Omega-Ω Notation, Theta-Θ Notation, Asymptotic Analysis, Properties of Notations, Commonly used Logarithms and Summations, Performance characteristics of algorithms, Master Theorem for Divide and Conquer, Divide and Conquer Master Theorem: Problems & Solutions, Master Theorem for Subtract and Conquer Recurrences, Method of Guessing and Confirming

2ndUnit

Unit 2: Tree algorithms

Tree algorithms:
What is a Tree? Glossary, Binary Trees, Types of Binary Trees, Properties of Binary Trees, Binary Tree Traversals, Generic Trees (N-ary Trees), Threaded Binary Tree Traversals, Expression Trees, Binary Search Trees (BSTs), Balanced Binary Search Trees, AVL (Adelson-Velskii and Landis) Trees

Graph Algorithms:
Introduction, Glossary, Applications of Graphs, Graph Representation, Graph Traversals, Topological Sort, Shortest Path Algorithms, Minimal Spanning Tree.

Selection Algorithms:
What are Selection Algorithms? Selection by Sorting, Partition-based Selection Algorithm, Linear Selection Algorithm - Median of Medians Algorithm, Finding the K Smallest Elements in Sorted Order.

3rdUnit

Unit 3: Algorithms Design Techniques

Algorithms Design Techniques:
Introduction, Classification, Classification by Implementation Method, Classification by Design Method.

Greedy Algorithms:
Introduction, Greedy Strategy, Elements of Greedy Algorithms, Advantages and Disadvantages of Greedy Method, Greedy Applications, Understanding Greedy Technique.

Divide and Conquer Algorithms:
Introduction, What is Divide and Conquer Strategy? Divide and Conquer Visualization, Understanding Divide and Conquer, Advantages of Divide and Conquer, Disadvantages of Divide and Conquer, Master Theorem, Divide and Conquer Applications.

Dynamic Programming:
Introduction, What is Dynamic Programming Strategy? Properties of Dynamic Programming Strategy, Problems which can be solved using Dynamic Programming, Dynamic Programming Approaches, Examples of Dynamic Programming Algorithms, Understanding Dynamic Programming, Longest Common Subsequence.

1stUnit

Unit 1: Swing, JDBC

Swing:
Need for swing components, Difference between AWT and swing, Components hierarchy, Panes, Swing components: Jlabel, JTextField and JPasswordField, JTextAres, JButton, JCheckBox, JRadioButton, JComboBox and JList

JDBC:
Introduction, JDBC Architecture, Types of Drivers, Statement, ResultSet, Read Only ResultSet, Updatable ResultSet, Forward Only ResultSet, Scrollable ResultSet, PreparedStatement, Connection Modes, SavePoint, Batch Updations, CallableStatement, BLOB & CLOB.

2ndUnit

Unit 2: Servlets, JSP

Servlets:
Introduction, Web application Architecture, Http Protocol & Http Methods, Web Server & Web Container, Servlet Interface, GenericServlet, HttpServlet, Servlet Life Cycle, ServletConfig, ServletContext, Servlet Communication, Session Tracking Mechanisms.

JSP:
Introduction, JSP LifeCycle, JSP Implicit Objects & Scopes, JSP Directives, JSP Scripting Elements, JSP Actions: Standard actions and customized actions.

3ndUnit

Unit 3: Java Beans

Java Beans:
Introduction, JavaBeans Properties, Examples.

Struts 2:
Basic MVC Architecture, Struts 2 framework features, Struts 2 MVC pattern, Request life cycle, Examples, Configuration Files, Actions, Interceptors, Results & Result Types, Value Stack/OGNL.

JSON:
Overview, Syntax, DataTypes, Objects, Schema, Comparison with XML, JSON with Java.

1stUnit

Unit 1: Introduction Network Models

Introduction Network Models:
Introduction to data communication, Components, Data Representation, Data Flow, Networks, Network Criteria, Physical Structures, Network types, Local Area Network, Wide Area Network, Switching, The Internet, Accessing the Internet, standards and administration Internet Standards. Network Models, Protocol layering, Scenarios, Principles of Protocol Layering, Logical Connections, TCP/IP Protocol Suite, Layered Architecture, Layers in the TCP/IP Protocol Suite, Encapsulation and Decapsulation, Addressing, Multiplexing and Demultiplexing. Detailed introduction to Physical Layer, Detailed introduction to Data-Link Layer, Detailed introduction to Network Layer, Detailed introduction to Transport Layer, Detailed introduction to Application Layer. Data and Signals, Analog and Digital Data, Analog and Digital Signals, Sine Wave Phase, Wavelength, Time and Frequency Domains, Composite Signals, Bandwidth, Digital Signal, Bit Rate, Bit Length, Transmission of Digital Signals, Transmission Impairments, Attenuation, Distortion, Noise, Data Rate Limits, Performance, Bandwidth, Throughput, Latency (Delay).

2ndUnit

Unit 2: Introduction to Physical Layer and Data-Link Layer

Introduction to Physical Layer and Data-Link Layer:
Digital Transmission digital-to-digital conversion, Line Coding, Line Coding Schemes, analog-to-digital conversion, Pulse Code Modulation (PCM), Transmission Modes, Parallel Transmission, Serial Transmission. Analog Transmission, digital-to-analog Conversion, Aspects of Digital-to-Analog Conversion, Amplitude Shift Keying, Frequency Shift Keying, Phase Shift Keying, analog-to-analog Conversion, Amplitude Modulation (AM), Frequency Modulation (FM), Phase Modulation (PM), Multiplexing, Frequency-Division Multiplexing, Wavelength-Division Multiplexing, Time-Division Multiplexing. Transmission Media, Guided Media, Twisted-Pair Cable, Coaxial Cable, Fiber-Optic Cable. Switching, Three Methods of Switching, Circuit Switched Networks, Packet Switching, Introduction to Data-Link Layer, Nodes and Links, Services, Two Sub-layers, Three Types of addresses, Address Resolution Protocol (ARP). Error Detection and Correction, introduction, Types of Errors, Redundancy, Detection versus Correction

3ndUnit

Unit 3: Network layer, Transport Layer

Network layer, Transport Layer
Media Access Control (MAC), random access, CSMA, CSMA/CD, CSMA/CA, controlled access, Reservation, Polling, Token Passing, channelization, FDMA, TDMA, CDMA.

Connecting Devices and Virtual LANs, connecting devices, Hubs, Link-Layer Switches, Routers, Introduction to Network Layer, network layer services, Packetizing, Routing and Forwarding, Other Services, IPv4 addresses, Address Space, Classful Addressing.

Unicast Routing, General Idea, Least-Cost Routing, Routing Algorithms, Distance-Vector Routing, Link-State Routing, Path-Vector Routing, Introduction to Transport Layer, Transport-Layer Services, Connectionless and Connection-Oriented Protocols.

Transport-Layer Protocols, Service, Port Numbers, User Datagram Protocol, User Datagram, UDP Services, UDP Applications, Transmission Control Protocol, TCP Services, TCP Features, Segment.

1stUnit

Unit 1: Introduction

Introduction:
The Nature of Software, Software Engineering, The Software Process, Generic Process Model, The Waterfall Model, Incremental Process Models, Evolutionary Process Models, Concurrent Models, Component-Based Development, The Unified Process Phases, Agile Development- Agility, Agile Process, Extreme Programming.

Requirement Analysis and System Modeling:
Requirements Engineering, Eliciting Requirements, SRS Validation, Components of SRS, Characteristics of SRS, Object-oriented design using the UML - Class diagram, Object diagram, Use case diagram, Sequence diagram, Collaboration diagram, State chart diagram, Activity diagram, Component diagram, Deployment diagram.

2ndUnit

Unit 2: System Design

System Design:
System/Software Design, Architectural Design, Low-Level Design Coupling and Cohesion, Functional-Oriented Versus The Object-Oriented Approach, Design Specifications, Verification for Design, Monitoring and Control for Design.

Software Measurement and Metrics:
Product Metrics – Measures, Metrics, and Indicators, Function-Based Metrics, Metrics for Object-Oriented Design, Operation-Oriented Metrics, User Interface Design Metrics, Metrics for Source Code, Halstead Metrics Applied to Testing, Metrics for Maintenance, Cyclomatic Complexity, Software Measurement - Size-Oriented, Function-Oriented Metrics, Metrics for Software Quality.

Software Project Management:
Estimation in Project Planning Process –Software Scope And Feasibility, Resource Estimation, Empirical Estimation Models – COCOMO II, Estimation for Agile Development, The Make/Buy Decision

Project Scheduling:
Basic Principles, Relationship between People and Effort, Effort Distribution, Time-Line Charts

3rdUnit

Unit 3: Risk Management

Risk Management :
Software Risks, Risk Identification, Risk Projection and Risk Refinement, RMMM Plan.

Software Quality Assurance:
Elements of SQA, SQA Tasks, Goals, and Metrics, Formal Approaches to SQA, Six Sigma, Software Reliability, The ISO 9000 Quality Standards, Capability Maturity Model.

Software Testing:
Verification and Validation, Introduction to Testing, Testing Principles, Testing Objectives, Test Oracles, Levels of Testing, White-Box Testing/Structural Testing, Functional/Black-Box Testing, Test Plan, Test-Case Design.

1stUnit

Unit 1: Field

Field:
Introduction to complex numbers, numbers in Python , Abstracting over fields, Playing with GF(2), Vector Space: Vectors are functions, Vector addition, Scalar-vector multiplication, Combining vector addition and scalar multiplication, Dictionary-based representations of vectors, Dot-product, Solving a triangular system of linear equations. Linear combination, Span, The geometry of sets of vectors, Vector spaces, Linear systems, homogeneous and otherwise.

2ndUnit

Unit 2: Matrix

Matrix:
Matrices as vectors, Transpose, Matrix-vector and vector-matrix multiplication in terms of linear combinations, Matrix-vector multiplication in terms of dot-products, Null space, Computing sparse matrix-vector product, Linear functions, Matrix-matrix multiplication, Inner product and outer product, From function inverse to matrix inverse.

Basis:
Coordinate systems, Two greedy algorithms for finding a set of generators, Minimum Spanning Forest and GF(2), Linear dependence, Basis , Unique representation, Change of basis, first look, Computational problems involving finding a basis.

Dimension:
Dimension and rank, Direct sum, Dimension and linear functions, The annihilator.

3rdUnit

Unit 3: Gaussian elimination

Gaussian elimination:
Echelon form, Gaussian elimination over GF (2), Solving a matrix-vector equation using Gaussian elimination, Finding a basis for the null space, Factoring integers

Inner Product:
The inner product for vectors over the reals, Orthogonality.

Orthogonalization:
Projection orthogonal to multiple vectors, Projecting orthogonal to mutually orthogonal vectors, Building an orthogonal set of generators, Orthogonal complement,
Eigenvector: Modeling discrete dynamic processes, Diagonalization of the Fibonacci matrix, Eigenvalues and eigenvectors, Coordinate representation in terms of eigenvectors, The Internet worm, Existence of eigenvalues, Markov chains, Modeling a web surfer: PageRank.

1stUnit

Unit 1: The .NET Framework

The .NET Framework:
.NET Languages, Common Language Runtime, .NET Class Library.

C# Language Basics:
Comments, Variables and Data Types, Variable Operations, Object-Based Manipulation, Conditional Logic, Loops, Methods, Classes, Value Types and Reference Types, Namespaces and Assemblies, Inheritance, Static Members, Casting Objects, Partial Classes.

ASP.NET:
Creating Websites, Anatomy of a Web Form - Page Directive, Doctype, Writing Code - Code-Behind Class, Adding Event Handlers, Anatomy of an ASP.NET Application - ASP.NET File Types, ASP.NET Web Folders.

HTML Server Controls:
View State, HTML Control Classes, HTML Control Events, HtmlControl Base Class, HtmlContainerControl Class, HtmlInputControl Class, Page Class, global.asax File, web.config File.

2ndUnit

Unit 2: Web Controls

Web Controls:
Web Control Classes, WebControl Base Class, List Controls, Table Controls, Web Control Events and AutoPostBack, Page Life Cycle.

State Management:
ViewState, Cross-Page Posting, Query String, Cookies, Session State, Configuring Session State, Application State.

Validation:
Validation Controls, Server-Side Validation, Client-Side Validation, HTML5 Validation, Manual Validation, Validation with Regular Expressions.

Rich Controls:
Calendar Control, AdRotator Control, MultiView Control.

Themes and Master Pages:
How Themes Work, Applying a Simple Theme, Handling Theme Conflicts, Simple Master Page and Content Page, Connecting Master pages and Content Pages, Master Page with Multiple Content Regions, Master Pages and Relative Paths

Website Navigation:
Site Maps, URL Mapping and Routing, SiteMapPath Control, TreeView Control, Menu Control.

3rdUnit

Unit 3: ADO.NET

ADO.NET:
Data Provider Model, Direct Data Access - Creating a Connection, Select Command, DataReader, Disconnected Data Access.

Data Binding:
Introduction, Single-Value Data Binding, Repeated-Value Data Binding, Data Source Controls – SqlDataSource.

Data Controls:
GridView, DetailsView, FormView

Working with XML:
XML Classes – XMLTextWriter, XMLTextReader.

Caching:
When to Use Caching, Output Caching, Data Caching.

LINQ:
Understanding LINQ, LINQ Basics.

ASP.NET AJAX:
ScriptManager, Partial Refreshes, Progress Notification, Timed Refreshes

1stUnit

Unit 1: What is Android

What is Android:
Obtaining the required tools, creating first android app, understanding the components of screen, adapting display orientation, action bar, Activities and Intents, Activity Lifecycle and Saving State, Basic Views: TextView, Button, ImageButton, EditText, CheckBox, ToggleButton, RadioButton, and RadioGroup Views, ProgressBar View, AutoCompleteTextView, TimePicker View, DatePicker View, ListView View, Spinner View.

2ndUnit

Unit 2: User Input Controls

User Input Controls:
User Input Controls, Menus, Screen Navigation, RecyclerView, Drawables, Themes and Styles, Material design, Providing resources for adaptive layouts, AsyncTask and AsyncTaskLoader, Connecting to the Internet, Broadcast receivers, Services, Notifications, Alarm managers, Transferring data efficiently.

3rdUnit

Unit 3: Data

Data :
Data - saving, retrieving, and loading: Overview to storing data, Shared preferences, SQLite primer, store data using SQLite database, ContentProviders, loaders to load and display data, Permissions, performance and security, Firebase and AdMob, Publish your app.

1stUnit

Unit 1: What Is AI

What Is AI:
Foundations, History and State of the Art of AI.

Intelligent Agents:
Agents and Environments, Nature of Environments, Structure of Agents.

Problem Solving by searching:
Problem-Solving Agents, Example Problems, Searching for Solutions, Uninformed Search Strategies, Informed (Heuristic) Search Strategies, Heuristic Functions.

2ndUnit

Unit 2: Learning from Examples

Learning from Examples :
Forms of Learning, Supervised Learning, Learning Decision Trees, Evaluating and Choosing the Best Hypothesis, Theory of Learning, Regression and Classification with Linear Models, Artificial Neural Networks, Nonparametric Models, Support Vector Machines, Ensemble Learning, Practical Machine Learning

3rdUnit

Unit 3: Learning probabilistic models

Learning probabilistic models
Statistical Learning, Learning with Complete Data, Learning with Hidden Variables: The EM Algorithm. Reinforcement learning: Passive Reinforcement Learning, Active Reinforcement Learning, Generalization in Reinforcement Learning, Policy Search, Applications of Reinforcement Learning.

4thPractical

Practical

Practical shall be implemented in LISP
1. Implement Breadth first search algorithm for Romanian map problem.
2. Implement Iterative deep depth first search for Romanian map problem.
3. Implement A* search algorithm for Romanian map problem.
4. Implement recursive best-first search algorithm for Romanian map problem.
5. Implement decision tree learning algorithm for the restaurant waiting problem.
6. Implement feed forward back propagation neural network learning algorithm for the restaurant waiting problem.
7. Implement Adaboost ensemble learning algorithm for the restaurant waiting problem.
8. Implement Naive Bayes’ learning algorithm for the restaurant waiting problem.
9. Implement passive reinforcement learning algorithm based on adaptive dynamic programming (ADP) for the 3 by 4 world problem
10. Implement passive reinforcement learning algorithm based on temporal differences (TD) for 3 by 4 world problem.

1stUnit

Unit 1: Introduction

Introduction:
Technical Summary of Linux Distributions, Managing Software

Single-Host Administration:
Managing Users and Groups, Booting and shutting down processes, File Systems, Core System Services, Process of configuring, compiling, Linux Kernel

Networking and Security:
TCP/IP for System Administrators, basic network Configuration, Linux Firewall (Netfilter), System and network security

2ndUnit

Unit 2: Internet Services

Internet Services Domain Name System (DNS), File Transfer Protocol (FTP), Apache web server, Simple Mail Transfer Protocol (SMTP), Post Office Protocol and Internet Mail Access Protocol (POP and IMAP), Secure Shell (SSH), Network Authentication, OpenLDAP Server, Samba and LDAP, Network authentication system (Kerberos), Domain Name Service (DNS), Security.

3rdUnit

Unit 3: Intranet Services

Intranet Services:
Network File System (NFS), Samba, Distributed File Systems (DFS), Network Information Service (NIS), Lightweight Directory Access Protocol (LDAP), Dynamic Host Configuration Protocol (DHCP), MySQL, LAMP Applications File Servers, Email Services, Chat Applications, Virtual Private Networking.

4thUnit

Unit 4: Practical

Practical:
- Practical shall be performed using any Linux Server (with 8GB RAM).
- Internet connection will be required so that Linux server (command line mode) can be connected to Internet.
1. Install DHCP Server in Ubuntu 16.04
2. Initial settings: Add a User, Network Settings, Change to static IP address, Disable IPv6 if not needed, Configure Services, display the list of services which are running, Stop and turn OFF auto-start setting for a service if you don’t need it, Sudo Settings
3. Configure NTP Server (NTPd), Install and Configure NTPd, Configure NTP Client (Ubuntu and Windows)
4. SSH Server : Password Authentication Configure SSH Server to manage a server from the remote computer, SSH Client : (Ubuntu and Windows)
5. Install DNS Server BIND, Configure DNS server which resolves domain name or IP address, Install BIND 9, Configure BIND, Limit ranges you allow to access if needed.
6. Configure DHCP Server, Configure DHCP (Dynamic Host Configuration Protocol) Server, Configure NFS Server to share directories on your Network, Configure NFS Client. (Ubuntu and Windows Client OS)
7. Configure LDAP Server, Configure LDAP Server in order to share users' accounts in your local networks, Add LDAP User Accounts in the OpenLDAP Server, Configure LDAP Client in order to share users' accounts in your local networks. Install phpLDAPadmin to operate LDAP server via Web browser.
8. Configure NIS Server in order to share users' accounts in your local networks, Configure NIS Client to bind NIS Server.
9. Install MySQL to configure database server, Install phpMyAdmin to operate MySQL on web browser from Clients.
10. Install Samba to share folders or files between Windows and Linux.

1stUnit

Unit 1: Software Testing and Introduction to quality

Software Testing and Introduction to quality :
Introduction, Nature of errors, an example for Testing, Definition of Quality , QA, QC, QM and SQA , Software Development Life Cycle, Software Quality Factors.

Verification and Validation :
Definition of V &V , Different types of V & V Mechanisms, Concepts of Software Reviews, Inspection and Walkthrough.

Software Testing Techniques:
Testing Fundamentals, Test Case Design, White Box Testing and its types, Black Box Testing and its types

2ndUnit

Unit 2: Software Testing Strategies

Software Testing Strategies:
Strategic Approach to Software Testing, Unit Testing, Integration Testing, Validation Testing, System Testing

Software Metrics:
Concept and Developing Metrics, Different types of Metrics, Complexity metrics

Defect Management:
Definition of Defects, Defect Management Process, Defect Reporting, Metrics Related to Defects, Using Defects for Process Improvement.

3rdUnit

Unit 3: Software Quality Assurance:

Software Quality Assurance:
Quality Concepts, Quality Movement, Background Issues, SQA activities, Software Reviews, Formal Technical Reviews, Formal approaches to SQA, Statistical Quality Assurance, Software Reliability, The ISO 9000 Quality Standards, SQA Plan , Six sigma, Informal Reviews

Quality Improvement:
Introduction, Pareto Diagrams, Cause-effect Diagrams, Scatter Diagrams, Run charts

Quality Costs:
Defining Quality Costs, Types of Quality Costs, Quality Cost Measurement, Utilizing Quality Costs for Decision-Making

4thUnit

Unit 4: Practical

Practical
1. Install Selenium IDE; Write a test suite containing minimum 4 test cases for different formats.
2. Conduct a test suite for any two web sites.
3. Install Selenium server (Selenium RC) and demonstrate it using a script in Java/PHP.
4. Write and test a program to login a specific web page.
5. Write and test a program to update 10 student records into table into Excel file.
6. Write and test a program to select the number of students who have scored more than 60 in any one subject (or all subjects).
7. Write and test a program to provide total number of objects present / available on the page.
8. Write and test a program to get the number of items in a list / combo box.
9. Write and test a program to count the number of check boxes on the page checked and unchecked count.
10. Load Testing using JMeter, Android Application testing using Appium Tools, Bugzilla Bug tracking tools.

1stUnit

Unit 1: Introduction

Introduction:
Security Trends, The OSI Security Architecture, Security Attacks, Security Services, Security Mechanisms

Classical Encryption Techniques :
Symmetric Cipher Model, Substitution Techniques, Transposition Techniques, Steganography, Block Cipher Principles, The Data Encryption Standard, The Strength of DES, AES (round details not expected), Multiple Encryption and Triple DES, Block Cipher Modes of Operation, Stream Ciphers.

Public-Key Cryptography and RSA:
Principles of Public-Key Cryptosystems, The RSA Algorithm

2ndUnit

Unit 2: Key Management

Key Management
Public-Key Cryptosystems, Key Management, Diffie-Hellman Key Exchange

Message Authentication and Hash Functions
Authentication Requirements, Authentication Functions, Message Authentication Codes, Hash Functions, Security of Hash Functions and Macs, Secure Hash Algorithm, HMAC

Digital Signatures and Authentication
Digital Signatures, Authentication Protocols, Digital Signature Standard

Authentication Applications:
Kerberos, X.509 Authentication, Public-Key Infrastructure

3rdUnit

Unit 3: Electronic Mail Security

Electronic Mail Security:
Pretty Good Privacy, S/MIME IP Security: Overview, Architecture, Authentication Header, Encapsulating Security Payload, Combining Security Associations, Key Management

Web Security:
Web Security Considerations, Secure Socket Layer and Transport Layer Security, Secure Electronic Transaction

Intrusion:
Intruders, Intrusion Techniques, Intrusion Detection

Malicious Software:
Viruses and Related Threats, Virus Countermeasures, DDOS

Firewalls:
Firewall Design Principles, Types of Firewalls

4thUnit

Practical

Practical :
1. Write programs to implement the following Substitution Cipher Techniques:
- Caesar Cipher
- Monoalphabetic Cipher
2. Write programs to implement the following Substitution Cipher Techniques:
- Vernam Cipher
- Playfair Cipher
3. Write programs to implement the following Transposition Cipher Techniques:
- Rail Fence Cipher
- Simple Columnar Technique
4. Write program to encrypt and decrypt strings using
- DES Algorithm
- AES Algorithm
5. Write a program to implement RSA algorithm to perform encryption / decryption of a given string.
6. Write a program to implement the Diffie-Hellman Key Agreement algorithm to generate symmetric keys.
7. Write a program to implement the MD5 algorithm compute the message digest.
8. Write a program to calculate HMAC-SHA1 Signature.
9. Write a program to implement SSL.
10. Configure Windows Firewall to block:
- A port
- An Program
- A website

1stUnit

Unit 1: IoT-An Architectural Overview

IoT-An Architectural Overview:
Building architecture, Main design principles and needed capabilities, An IoT architecture outline, standards considerations.

IoT Architecture-State of the Art:
Introduction, State of the art, Reference Model and architecture, IoT reference Model - IoT Reference Architecture Introduction, Functional View, Information View, Deployment and Operational View, Other Relevant architectural views.

2ndUnit

Unit 2: IoT Data Link Layer and Network Layer Protocols

IoT Data Link Layer and Network Layer Protocols:
PHY/MAC Layer(3GPP MTC, IEEE 802.11, IEEE 802.15), Wireless HART,Z-Wave, Bluetooth Low Energy, Zigbee Smart Energy DASH7 Network Layer:IPv4, IPv6, 6LoWPAN, 6TiSCH,ND, DHCP, ICMP, RPL, CORPL, CARP

Transport layer protocols:
Transport Layer (TCP, MPTCP, UDP, DCCP, SCTP)-(TLS, DTLS)

3rdUnit

Unit 3: Session layer

Session layer:
Session Layer-HTTP, CoAP, XMPP, AMQP, MQTT

Service layer protocols:
Service Layer -oneM2M, ETSI M2M, OMA, BBF

4thUnit

Practical

Practical:
1. a) Edit text files with nano and cat editor, Learn sudo privileges and Unix shell commands such as cd , ls , cat, etc
b) Learn to set dynamic and static IP. Connect to and Ethernet and WiFi network. Learn to vnc and ssh into a raspberry pi using vnc and putty from a different computer on the network.
c) Write a basic bash script to open programs in kiosk mode. Learn how to autostart programs on boot.
2. Run the node red editor and run simple programs and trigger gpios. Use basic nodes such as inject, debug, gpio
3. Open the python idle editor and run simple Python scripts such as to print Fibonacci numbers, string functions. Learn how to install modules using Pip and write functions
4. Setup a physical button switch and trigger an led in node red and python w debounce
5. Write simple JavaScript functions in Node-Red simple HTTP server page using node red
6. Setup a TCP server and client on a raspberry pi using Python modules to send messages and execute shell commands from within python such as starting another application
7. Trigger a set of led Gpios on the pi via a Python Flask web server
8. Interface the raspberry pi with a 16x2 LCD display and print values.
9. Setup a Mosquitto MQTT server and client and write a Python script to communicate data between Pi's.
10. Interface with an Accelerometer Gyro Mpu6050 on the i2c bus and send sensor values over the internet via mqtt.

1stUnit

Unit 1: Web services basics

Web services basics :
What Are Web Services? Types of Web Services Distributed computing infrastructure, overview of XML, SOAP, Building Web Services with JAX-WS, Registering and Discovering Web Services, Service Oriented Architecture, Web Services Development Life Cycle, Developing and consuming simple Web Services across platform.

2ndUnit

Unit 2: The REST Architectural style

The REST Architectural style :
Introducing HTTP, The core architectural elements of a RESTful system, Description and discovery of RESTful web services, Java tools and frameworks for building RESTful web services, JSON message format and tools and frameworks around JSON, Build RESTful web services with JAX-RS APIs, The Description and Discovery of RESTful Web Services, Design guidelines for building RESTful web services, Secure RESTful web Services.

3rdUnit

Unit 3: Developing Service-Oriented Applications with WCF

Developing Service-Oriented Applications with WCF:
What Is Windows Communication Foundation, Fundamental Windows Communication Foundation Concepts, Windows Communication Foundation Architecture, WCF and .NET Framework Client Profile, Basic WCF Programming, WCF Feature Details. Web Service QoS

4thUnit

Practical

Practical:
1. Write a program to implement to create a simple web service that converts the temperature from Fahrenheit to Celsius and vice a versa.
2. Write a program to implement the operation can receive request and will return a response in two ways. a) One - Way operation b) Request –Response
3. Write a program to implement business UDDI Registry entry.
4. Develop client which consumes web services developed in different platform.
5. Write a JAX-WS web service to perform the following operations. Define a Servlet / JSP that consumes the web service.
6. Define a web service method that returns the contents of a database in a JSON string. The contents should be displayed in a tabular format.
7. Define a RESTful web service that accepts the details to be stored in a database and performs CRUD operation.
8. Implement a typical service and a typical client using WCF.
9. Use WCF to create a basic ASP.NET Asynchronous JavaScript and XML (AJAX) service.
10. Demonstrates using the binding attribute of an endpoint element in WCF.

1stUnit

Unit 1: Mathematics for Computer Graphics, DirectX Kickstart

Cartesian Coordinate system :
The Cartesian XY-plane, Function Graphs, Geometric Shapes, Polygonal Shapes, Areas of Shapes, Theorem of Pythagoras in 2D, Coordinates, Theorem of Pythagoras in 3D, 3D Polygons, Euler’s Rule.

Vectors :
Vector Manipulation, multiplying a Vector by a Scalar, Vector Addition and Subtraction, Position Vectors, Unit Vectors, Cartesian Vectors, Vector Multiplication, Scalar Product, Example of the Dot Product, The Dot Product in Lighting Calculations, The Dot Product in Back-Face Detection, The Vector Product, The Right-Hand Rule, deriving a Unit Normal Vector for a Triangle Areas, Calculating 2D Areas.

Transformations :
2D Transformations, Matrices, Homogeneous Coordinates, 3D Transformations, Change of Axes, Direction Cosines, rotating a Point about an Arbitrary Axis, Transforming Vectors, Determinants, Perspective Projection, Interpolation.

DirectX :
Understanding GPU and GPU architectures. How they are different from CPU Architectures? Understanding how to solve by GPU?

2ndUnit

Unit 2: DirectX Pipeline and Programming, Interpolation and Character Animation

Introduction To DirectX 11 :
COM, Textures and Resources Formats, The swap chain and Page flipping, Depth Buffering, Texture Resource Views, Multisampling Theory and MS in Direct3D, Feature Levels.

Direct3D 11 Rendering Pipeline :
Overview, Input Assembler Stage (IA), Vertex Shader Stage (VS), The Tessellation Stage (TS), Geometry Shader Stage (GS), Pixel Shader Stage (PS), Output merger Stage (OM) Understanding Meshes or Objects, Texturing, Lighting, Blending.

Interpolation and Character Animation :
Trigonometry:
The Trigonometric Ratios, Inverse Trigonometric Ratios, Trigonometric Relationships, The Sine Rule, The Cosine Rule, Compound Angles, Perimeter Relationships.

Interpolation:
Linear Interpolant, Non-Linear Interpolation, Trigonometric Interpolation, Cubic Interpolation, Interpolating Vectors, Interpolating Quaternions. Curves: Circle, Bezier, B-Splines.

Analytic Geometry:
Review of Geometry, 2D Analytic Geometry, Intersection Points, Point in Triangle, and Intersection of circle with straight line.

3rdUnit

Unit 3: Introduction to Rendering Engines

Introduction to Rendering Engines:
Understanding the current market Rendering Engines. Understanding AR, VR and MR.Depth Mappers, Mobile Phones, Smart Glasses, HMD’s.

Unity Engine:
Multi-platform publishing, VR + AR: Introduction and working in Unity, 2D, Graphics, Physics, Scripting, Animation, Timeline, Multiplayer and Networking, UI, Navigation and Pathfinding, XR, Publishing.
Scripting: Scripting Overview, Scripting Tools and Event Overview XR: VR, AR, MR, Conceptual Differences. SDK, Devices

4thUnit

Practical

Practical:
1. Setup DirectX 11, Window Framework and Initialize Direct3D Device
2. Buffers, Shaders and HLSL (Draw a triangle using Direct3D 11)
3. Texturing (Texture the Triangle using Direct 3D 11)
4. Lightning (Programmable Diffuse Lightning using Direct3D 11)
5. Specular Lightning (Programmable Spot Lightning using Direct3D 11)
6.Loading models into DirectX 11 and rendering.

1stUnit

Unit 1: Introduction

Introduction:
Introduction to Sensor Networks, unique constraints and challenges. Advantage of Sensor Networks, Applications of Sensor Networks, Mobile Adhoc NETworks (MANETs) and Wireless Sensor Networks, Enabling technologies for Wireless Sensor Networks.

Sensor Node Hardware and Network Architecture:
Single-node architecture, Hardware components & design constraints, Operating systems and execution environments, introduction to TinyOS and nesC. Network architecture, Optimization goals and figures of merit, Design principles for WSNs, Service interfaces of WSNs, Gateway concepts.

2ndUnit

Unit 2: Medium Access Control Protocols

Medium Access Control Protocols:
Fundamentals of MAC Protocols, MAC Protocols for WSNs, Sensor-MAC Case Study.

Routing Protocols:
Data Dissemination and Gathering, Routing Challenges and Design Issues in Wireless Sensor Networks, Routing Strategies in Wireless Sensor Networks.

Transport Control Protocols:
Traditional Transport Control Protocols, Transport Protocol Design Issues, Examples of Existing Transport Control Protocols, Performance of Transport Control Protocols.

3rdUnit

Unit 3: Introduction, Wireless Transmission and Medium Access Control:

Introduction, Wireless Transmission and Medium Access Control:
Applications, A short history of wireless communication.

Wireless Transmission:
Frequency for radio transmission, Signals, Antennas, Signal propagation, Multiplexing, Modulation, Spread spectrum, Cellular systems.

Telecommunication, Satellite and Broadcast Systems: GSM:
Mobile services, System architecture, Radio interface, Protocols, Localization And Calling, Handover, security, New data services; DECT: System architecture, Protocol architecture; ETRA, UMTS and IMT- 2000. Satellite Systems: History, Applications, Basics: GEO, LEO, MEO; Routing, Localization, Handover.

4thUnit

Unit 4: Practical

Practical:
Practical experiments require software tools like INET Framework for OMNeT++, NetSim, TOSSIM, Cisco packet tracer 6.0 and higher version.
1. Understanding the Sensor Node Hardware. (For Eg. Sensors, Nodes(Sensor mote), Base Station, Graphical User Interface.)
2. Exploring and understanding TinyOS computational concepts:- Events, Commands and Task.
a. nesC model
b. nesC Components
3. Understanding TOSSIM for
a. Mote-mote radio communication
b. Mote-PC serial communication
4. Create and simulate a simple adhoc network
5. Understanding, Reading and Analyzing Routing Table of a network.
6. Create a basic MANET implementation simulation for Packet animation and Packet Trace.
7. Implement a Wireless sensor network simulation.
8. Create MAC protocol simulation implementation for wireless sensor Network.
9. Simulate Mobile Adhoc Network with Directional Antenna
10. Create a mobile network using Cell Tower, Central Office Server, Web browser and Web Server. Simulate connection between them.

1stUnit

Unit 1: Introduction to Cloud Computing

Introduction to Cloud Computing:
Introduction to Cloud Computing, Characteristics and benefits of Cloud Computing, Basic concepts of Distributed Systems, Web 2.0, Service-Oriented Computing, Utility-Oriented Computing. Elements of Parallel Computing. Elements of Distributed Computing. Technologies for Distributed Computing. Cloud Computing Architecture. The cloud reference model. Infrastructure as a service. Platform as a service. Software as a service. Types of clouds.

2ndUnit

Unit 2: Virtualization and Cloud Computing

Virtualization and Cloud Computing
Characteristics of Virtualized Environments. Taxonomy of Virtualization Techniques. Virtualization and Cloud Computing. Pros and Cons of Virtualization. Virtualization using KVM, Creating virtual machines, oVirt - management tool for virtualization environment. Open challenges of Cloud Computing.

3rdUnit

Unit 3: Introduction to OpenStack

Introduction to OpenStack:
Introduction to OpenStack, OpenStack test-drive, Basic OpenStack operations, OpenStack CLI and APIs, Tenant model operations, Quotas, Private cloud building blocks, Controller deployment, Networking deployment, Block Storage deployment, Compute deployment, deploying and utilizing OpenStack in production environments, Building a production environment, Application or chestration using OpenStack Heat.

4thUnit

Unit 4: Practical

Practical:
1. Study and implementation of Infrastructure as a Service.
2. Installation and Configuration of virtualization using KVM.
3. Study and implementation of Infrastructure as a Service.
4. Study and implementation of Storage as a Service.
5. Study and implementation of identity management.
6. Study Cloud Security management.
7. Write a program for web feed.
8. Study and implementation of Single-Sing-On.
9. User Management in Cloud.
10. Case study on Amazon EC2/Microsoft Azure/Google Cloud Platform.

1stUnit

Unit 1: Computer Forensics

Computer Forensics
Introduction to Computer Forensics and standard procedure, Incident Verification and System Identification ,Recovery of Erased and damaged data, Disk Imaging and Preservation, Data Encryption and Compression, Automated Search Techniques, Forensics Software

Network Forensic :
Introduction to Network Forensics and tracking network traffic, Reviewing Network Logs, Network Forensics Tools, Performing Live Acquisitions, Order of Volatility, Standard Procedure.

Cell Phone and Mobile Device Forensics :
Overview, Acquisition Procedures for Cell Phones and Mobile Devices.

2ndUnit

Unit 2: Internet Forensic

Internet Forensic:
Introduction to Internet Forensics, World Wide Web Threats, Hacking and Illegal access, Obscene and Incident transmission, Domain Name Ownership Investigation, Reconstructing past internet activities and events

E-mail Forensics:
e-mail analysis, e-mail headers and spoofing, Laws against e-mail Crime, Messenger Forensics: Yahoo Messenger.

Social Media Forensics:
Social Media Investigations

Browser Forensics:
Cookie Storage and Analysis, Analyzing Cache and temporary internet files, Web browsing activity reconstruction.

3rdUnit

Unit 3: Investigation, Evidence presentation and Legal aspects of Digital Forensics

Investigation, Evidence presentation and Legal aspects of Digital Forensics:
Authorization to collect the evidence , Acquisition of Evidence, Authentication of the evidence, Analysis of the evidence, Reporting on the findings, Testimony.

Introduction to Legal aspects of Digital Forensics:
Laws & regulations, Information Technology Act, Giving Evidence in court, Case Study – Cyber Crime cases, Case Study – Cyber Crime cases

4thUnit

Unit 4: Practical

Practical:
1. Creating a Forensic Image using FTK Imager/Encase Imager :
a. Creating Forensic Image
b. Check Integrity of Data
c. Analyze Forensic Image
2. Data Acquisition:
a. Perform data acquisition using:
b. USB Write Blocker + Encase Imager
c. SATA Write Blocker + Encase Imager
d. Falcon Imaging Device
3. Forensics Case Study: Solve the Case study (image file) provide in lab using Encase Investigator or Autopsy
4. Capturing and analyzing network packets using Wireshark (Fundamentals) :
a. Identification the live network
b. Capture Packets
c. Analyze the captured packets
5. Analyze the packets provided in lab and solve the questions using Wireshark :
a. What web server software is used by www.snopes.com?
b. About what cell phone problem is the client concerned?
c. According to Zillow, what instrument will Ryan learn to play?
d. How many web servers are running Apache?
e. What hosts (IP addresses) think that jokes are more entertaining when they are explained?
6. Using Sysinternals tools for Network Tracking and Process Monitoring :
a. Check Sysinternals tools
b. Monitor Live Processes
c. Capture RAM
d. Capture TCP/UDP packets
e. Monitor Hard Disk
f. Monitor Virtual Memory
g. Monitor Cache Memory
7. Recovering and Inspecting deleted files
a. Check for Deleted Files
b. Recover the Deleted Files
c. Analyzing and Inspecting the recovered files
d. Perform this using recovery option in ENCASE and also Perform manually through command line
8. Acquisition of Cell phones and Mobile devices
9. Email Forensics
a. Mail Service Providers
b. Email protocols
c. Recovering emails
d. Analyzing email header
10. Web Browser Forensics
a. Web Browser working
b. Forensics activities on browser
c. Cache / Cookies analysis
d. Last Internet activity

1stUnit

Unit 1: Introduction to Information Retrieval

Introduction to Information Retrieval:
Introduction, History of IR, Components of IR, and Issues related to IR, Boolean retrieval, Dictionaries and tolerant retrieval.

2ndUnit

Unit 2: Link Analysis and Specialized Search

Link Analysis and Specialized Search:
Link Analysis, hubs and authorities, Page Rank and HITS algorithms, Similarity, Hadoop & Map Reduce, Evaluation, Personalized search, Collaborative filtering and content-based recommendation of documents and products, handling “invisible” Web, Snippet generation, Summarization, Question Answering, Cross- Lingual Retrieval.

3rdUnit

Unit 3: Web Search Engine

Web Search Engine:
Web search overview, web structure, the user, paid placement, search engine optimization/spam, Web size measurement, search engine optimization/spam, Web Search Architectures.

XML retrieval:
Basic XML concepts, Challenges in XML retrieval, A vector space model for XML retrieval, Evaluation of XML retrieval, Text-centric versus data-centric XML retrieval.

4thUnit

Unit 4: Practical

Practical:
Practical may be done using software/tools like Python / Java / Hadoop
1. Write a program to demonstrate bitwise operation.
2. Implement Page Rank Algorithm.
3. Implement Dynamic programming algorithm for computing the edit distance between strings s1 and s2. (Hint. Levenshtein Distance)
4. Write a program to Compute Similarity between two text documents.
5. Write a map-reduce program to count the number of occurrences of each alphabetic character in the given dataset. The count for each letter should be case-insensitive (i.e., include both upper-case and lower-case versions of the letter; Ignore non-alphabetic characters).
6. Implement a basic IR system using Lucene.
7. Write a program for Pre-processing of a Text Document: stop word removal.
8. Write a program for mining Twitter to identify tweets for a specific period and identify trends and named entities.
9. Write a program to implement simple web crawler.
10. Write a program to parse XML text, generate Web graph and compute topic specific page rank.

1stUnit

Unit 1: Introduction to Image-processing System

Introduction to Image-processing System:
Introduction, Image Sampling, Quantization, Resolution, Human Visual Systems, Elements of an Image-processing System, Applications of Digital Image Processing

2D Signals and Systems:
2D signals, separable sequence, periodic sequence, 2D systems, classification of 2D systems, 2D Digital filter

Convolution and Correlation:
2D Convolution through graphical method, Convolution through 2D Z—transform, 2D Convolution through matrix analysis, Circular Convolution, Applications of Circular Convolution, 2D Correlation.

Image Transforms:
Need for transform, image transforms, Fourier transform, 2D Discrete Fourier Transform, Properties of 2D DFT, Importance of Phase, Walsh transform, Hadamard transform, Haar transform, Slant transform, Discrete Cosine transform, KL transform

2ndUnit

Unit 2: Image Enhancement

Image Enhancement:
Image Enhancement in spatial domain, Enhancement trough Point operations, Histogram manipulation, Linear and nonlinear Gray Level Transformation, local or neighborhood operation, Median Filter, Spatial domain High pass filtering, Bit-plane slicing, Image Enhancement in frequency domain, Homomorphic filter, Zooming operation, Image Arithmetic

Binary Image processing:
Mathematical morphology, Structuring elements, Morphological image processing, Logical operations, Morphological operations, Dilation and Erosion, Distance Transform

Colour Image processing :
Colour images, Colour Model, Colour image quantization, Histogram of a colour image.

3rdUnit

Unit 3: Image Segmentation

Image Segmentation:
Image segmentation techniques, Region approach, Clustering techniques, Thresholding, Edge-based segmentation, Edge detection, Edge Linking, Hough Transform

Image Compression:
Need for image compression, Redundancy in images, Image-compression scheme, Fundamentals of Information Theory, Run-length coding, Shannon-Fano coding, Huffman Coding, Arithmetic Coding, Transform-based compression, Image-compression standard

4thUnit

Unit 4: Practical

Practical:
Practical need to be performed using Scilab under Linux or Windows
1. 2D Linear Convolution, Circular Convolution between two 2D matrices
2. Circular Convolution expressed as linear convolution plus alias
3. Linear Cross correlation of a 2D matrix, Circular correlation between two signals and Linear auto correlation of a 2D matrix, Linear Cross correlation of a 2D matrix
4. DFT of 4x4 gray scale image
5. Compute discrete cosine transform, Program to perform KL transform for the given 2D matrix
6. Brightness enhancement of an image, Contrast Manipulation, image negative
7. Perform threshold operation, perform gray level slicing without background
8. Image Segmentation
9. Image Compression
10. Binary Image Processing and Colour Image processing

1stUnit

Unit 1: Introduction to Data Science

Introduction to Data Science:
What is Data? Different kinds of data, Introduction to high level programming language + Integrated Development Environment (IDE), Exploratory Data Analysis (EDA) + Data Visualization, Different types of data sources.

Data Management:
Data Collection, Data cleaning/extraction, Data analysis & Modeling

2ndUnit

Unit 2: Data Curation

Data Curation:
Query languages and Operations to specify and transform data, Structured/schema based systems as users and acquirers of data Semi-structured systems as users and acquirers of data, Unstructured systems in the acquisition and structuring of data, Security and ethical considerations in relation to authenticating and authorizing access to data on remote systems, Software development tools, Large scale data systems, Amazon Web Services(AWS).

3rdUnit

Unit 3: Statistical Modelling and Machine Learning

Introduction to model selection:
Regularization, bias/variance tradeoff e.g. parsimony, AIC, BIC, Cross validation, Ridge regressions and penalized regression e.g. LASSO.

Data transformations Dimension reduction, Feature extraction, Smoothing and aggregating

Supervised Learning:
Regression, linear models, Regression trees, Time-series Analysis, Forecasting, Classification: classification trees, Logistic regression, separating hyperplanes, k-NN

Unsupervised Learning:
Principal Components Analysis (PCA), k-means clustering, Hierarchical clustering, Ensemble methods

4thUnit

Unit 4: Practical

Practical:
Practical shall be performed using R
1. Practical of Data collection, Data curation and management for Unstructured data (NoSQL)
2. Practical of Data collection, Data curation and management for Large-scale Data system (such asMongoDB)
3. Practical of Principal Component Analysis
4. Practical of Clustering
5. Practical of Time-series forecasting
6. Practical of Simple/Multiple Linear Regression
7. Practical of Logistics Regression
8. Practical of Hypothesis testing
9. Practical of Analysis of Variance
10. Practical of Decision Tree

1stUnit

Unit 1: Information Security : Attacks and Vulnerabilities

Introduction to information security:
Asset, Access Control, CIA, Authentication, Authorization, Risk, Threat, Vulnerability, Attack, Attack Surface, Malware, Security-Functionality-Ease of Use Triangle

Types of malware:
Worms, viruses, Trojans, Spyware, Rootkits

Types of vulnerabilities : OWASP Top 10 :
cross-site scripting (XSS), cross site request forgery (CSRF/XSRF), SQL injection, input parameter manipulation, broken authentication, sensitive information disclosure, XML External Entities, Broken access control, Security Misconfiguration, Using components with known vulnerabilities, Insufficient Logging and monitoring, OWASP Mobile Top 10, CVE Database

Types of attacks and their common prevention mechanisms
Keystroke Logging, Denial of Service (DoS /DDoS), Waterhole attack, brute force, phishing and fake WAP, Eavesdropping, Man-in-the-middle, Session Hijacking, Clickjacking, Cookie Theft, URL Obfuscation, buffer overflow, DNS poisoning, ARP poisoning, Identity Theft, IoT Attacks, BOTs and BOTNETs

Case-studies:
Recent attacks – Yahoo, Adult Friend Finder, eBay, Equifax, WannaCry, Target Stores, Uber, JP Morgan Chase, Bad Rabbit

2ndUnit

Unit 2: Ethical Hacking – I (Introduction and pre-attack)

Introduction
Black Hat vs. Gray Hat vs. White Hat (Ethical) hacking, Why is Ethical hacking needed?, How is Ethical hacking different from security auditing and digital forensics?, Signing NDA, Compliance and Regulatory concerns, Black box vs. White box vs. Black box, Vulnerability assessment and Penetration Testing.

Approach : Planning
Threat Modeling, set up security verification standards, Set up security testing plan – When, which systems/apps, understanding functionality, black/gray/white, authenticated vs. unauthenticated, internal vs. external PT, Information gathering, Perform Manual and automated (Tools: WebInspect/Qualys, Nessus, Proxies, Metasploit) VA and PT, How WebInspect/Qualys tools work: Crawling/Spidering, requests forging, pattern matching to known vulnerability database and Analyzing results, Preparing report, Fixing security gaps following the report

Enterprise strategy:
Repeated PT, approval by security testing team, Continuous Application Security Testing,

Phases:
Reconnaissance/foot-printing/Enumeration, Phases: Scanning, Sniffing

3rdUnit

Unit 3: Ethical Hacking :Enterprise Security

Phases : Gaining and Maintaining Access : Systems hacking :
Windows and Linux – Metasploit and Kali Linux, Keylogging, Buffer Overflows, Privilege Escalation, Network hacking - ARP Poisoning, Password Cracking, WEP Vulnerabilities, MAC Spoofing, MAC Flooding, IPSpoofing, SYN Flooding, Smurf attack, Applications hacking : SMTP/Email-based attacks, VOIP vulnerabilities, Directory traversal, Input Manipulation, Brute force attack, Unsecured login mechanisms, SQL injection, XSS, Mobile apps security, Malware analysis : Netcat Trojan, wrapping definition, reverse engineering Phases : Covering your tracks : Steganography, Event Logs alteration Additional Security Mechanisms : IDS/IPS, Honeypots and evasion techniques, Secure Code Reviews (Fortify tool, OWASP Secure Coding Guidelines)

4thUnit

Unit 4: Practical

Practical:
1. Use Google and Whois for Reconnaissance
2. a. Use CrypTool to encrypt and decrypt passwords using RC4 algorithm
b. Use Cain and Abel for cracking Windows account password using Dictionary attack and to decode wireless network passwords
3. a. Run and analyze the output of following commands in Linux – ifconfig, ping, netstat, traceroute
b. Perform ARP Poisoning in Windows
4. Use NMap scanner to perform port scanning of various forms – ACK, SYN, FIN, NULL, XMAS
5. a. Use Wireshark (Sniffer) to capture network traffic and analyse
b. Use Nemesy to launch DoS attack
6. Simulate persistent cross-site scripting attack
7. Session impersonation using Firefox and Tamper Data add-on
8. Perform SQL injection attack
9. Create a simple keylogger using python
10. Using Metasploit to exploit (Kali Linux)

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