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C Syllabus

Basics of C

S.No	Topic	Math Concept	Connection to Previous Topic
1	Introduction to C	Arithmetic operations	Foundation for all programming concepts.
2	Variables and Data Types	Number systems (integers, floats)	Builds on arithmetic operations to handle data.
3	Control Structures	Conditional logic	Uses variables and arithmetic to implement decision-making.
4	Loops	Sequences and series	Builds on control structures to handle repetitive tasks.
5	Functions	Modular arithmetic	Uses loops and control structures to modularize code.

Arrays and Strings

S.No	Topic	Math Concept	Connection to Previous Topic
6	1D Arrays	Linear algebra (vectors)	Builds on loops and functions to handle collections of data.
7	2D Arrays	Matrices	Uses 1D arrays to handle multi-dimensional data.
8	Strings	Sequences and patterns	Builds on arrays to handle character data.
9	String Functions	Pattern matching	Uses string manipulation to solve real-world problems.
10	Array and String Problems	Combinatorics (permutations)	Builds on arrays and strings to solve complex problems.

Pointers and Dynamic Memory

S.No	Topic	Math Concept	Connection to Previous Topic
11	Pointers Basics	Number theory (addresses)	Builds on variables and functions to handle memory addresses.
12	Pointer Arithmetic	Arithmetic operations	Uses pointers to manipulate arrays efficiently.
13	Dynamic Memory Allocation	Number theory (prime numbers)	Builds on pointers to handle memory dynamically.
14	Pointer and Array Problems	Linear algebra (vectors)	Uses pointers and arrays to solve advanced problems.
15	File Handling	Data representation	Builds on pointers and arrays to manage external data.

Advanced C Concepts

S.No	Topic	Math Concept	Connection to Previous Topic
16	Structures	Geometry (shapes)	Builds on data types to handle complex data structures.
17	Unions	Data representation	Uses structures to handle memory-efficient data storage.
18	Recursion	Sequences and series	Builds on functions to solve problems using recursion.
19	Advanced Recursion	Combinatorics (Fibonacci)	Uses recursion to solve sequence-based problems.
20	Final Project	Problem-solving	Integrates all previous topics into a single project.

C++ Syllabus

C++ Basics

S.No	Topic	Math Concept	Connection to Previous Topic
1	Introduction to C++	Arithmetic operations	Foundation for all programming concepts.
2	Variables and Data Types	Number systems (integers, floats)	Builds on arithmetic operations to handle data.
3	Control Structures	Conditional logic	Uses variables and arithmetic to implement decision-making.
4	Loops	Sequences and series	Builds on control structures to handle repetitive tasks.
5	Functions	Modular arithmetic	Uses loops and control structures to modularize code.
6	Function Overloading	Polymorphism	Builds on functions to handle multiple operations with the same name.
7	References and Pointers	Number theory (addresses)	Uses functions to handle memory addresses efficiently.
8	Arrays	Linear algebra (vectors)	Builds on loops and functions to handle collections of data.
9	2D Arrays	Matrices	Uses 1D arrays to handle multi-dimensional data.
10	Strings	Sequences and patterns	Builds on arrays to handle character data.

Object-Oriented Programming (OOP)

S.No	Topic	Math Concept	Connection to Previous Topic
11	Classes and Objects	Geometry (shapes)	Builds on functions to create reusable and modular code.
12	Constructors and Destructors	Initialization and cleanup	Uses classes to handle object initialization and cleanup.
13	Encapsulation	Data hiding	Builds on classes to protect data from unauthorized access.
14	Inheritance	Hierarchical relationships	Uses classes to create hierarchical relationships.
15	Polymorphism	Overriding and overloading	Builds on inheritance to implement runtime polymorphism.
16	Abstract Classes	Abstract concepts	Uses polymorphism to define abstract concepts.
17	Operator Overloading	Custom operations	Builds on functions to define custom operations.
18	Friend Functions	Access control	Uses classes to allow external functions access to private members.
19	Static Members	Shared data	Builds on classes to handle shared data among objects.
20	OOP Project	Problem-solving	Integrates all OOP concepts into a single project.

STL and Advanced C++

S.No	Topic	Math Concept	Connection to Previous Topic
21	STL: Vectors	Linear algebra (vectors)	Builds on arrays to handle dynamic collections of data.
22	STL: Pairs and Sets	Combinatorics (unique elements)	Uses vectors to handle unique and sorted data.
23	STL: Maps	Key-value pairs	Builds on sets to handle key-value pairs.
24	STL: Queues and Stacks	LIFO and FIFO structures	Uses vectors to handle LIFO and FIFO structures.
25	STL: Algorithms	Sorting and searching	Builds on STL containers to implement efficient algorithms.
26	Bit Manipulation	Binary numbers, bitwise operations	Uses loops and logic to solve problems efficiently at the bit level.
27	Templates	Generic programming	Builds on functions to handle generic data types.
28	Exception Handling	Error handling	Uses functions to handle runtime errors.
29	File Handling	Data representation	Builds on arrays and pointers to manage external data.
30	STL Project	Problem-solving	Integrates all STL concepts into a single project.

Advanced Topics

S.No	Topic	Math Concept	Connection to Previous Topic
31	Lambda Expressions	Functional programming	Builds on STL algorithms to implement functional programming.
32	Multithreading	Parallel processing	Uses functions to handle concurrent execution.
33	Smart Pointers	Memory management	Builds on pointers to handle memory automatically.
34	Move Semantics	Efficient resource management	Uses pointers to optimize resource handling.
35	STL: Advanced Containers	Graph theory (trees, networks)	Builds on STL containers to handle complex data structures.
36	STL: Custom Comparators	Sorting and ordering	Uses STL algorithms to implement custom sorting logic.
37	STL: Advanced Algorithms	Combinatorics (permutations)	Builds on STL algorithms to solve complex problems.
38	STL: Numeric Algorithms	Number theory (GCD, LCM)	Uses STL algorithms to solve number theory problems.
39	STL: String Algorithms	Pattern matching	Builds on STL algorithms to handle string operations.
40	Final Project	Problem-solving	Integrates all C++ concepts into a single project.

DSA Syllabus

Arrays and Linked Lists

S.No	Topic	Math Concept	Connection to Previous Topic
1	Introduction to Arrays	Linear algebra (vectors)	Foundation for all data structures.
2	Array Operations	Sequences and series	Builds on basic array operations to handle data manipulation.
3	2D Arrays	Matrices	Uses 1D arrays to handle multi-dimensional data.
4	Introduction to Linked Lists	Number theory (addresses)	Builds on arrays to handle dynamic data structures.
5	Linked List Operations	Sequences and patterns	Uses linked lists to solve complex problems.
6	Doubly Linked Lists	Hierarchical relationships	Builds on singly linked lists to handle bidirectional traversal.
7	Circular Linked Lists	Cyclic structures	Uses linked lists to handle cyclic data structures.
8	Array and Linked List Problems	Combinatorics (permutations)	Builds on arrays and linked lists to solve advanced problems.
9	Dynamic Arrays	Linear algebra (vectors)	Uses arrays to handle resizable data structures.
10	Final Project	Problem-solving	Integrates all array and linked list concepts into a single project.

Stacks and Queues

S.No	Topic	Math Concept	Connection to Previous Topic
11	Introduction to Stacks	LIFO (Last In First Out)	Builds on arrays to handle LIFO structures.
12	Stack Operations	Algebra (expressions)	Uses stacks to solve expression evaluation problems.
13	Introduction to Queues	FIFO (First In First Out)	Builds on arrays to handle FIFO structures.
14	Queue Operations	Sequences and series	Uses queues to handle cyclic data structures.
15	Priority Queues	Sorting and ordering	Builds on queues to handle prioritized data.
16	Stack and Queue Problems	Combinatorics (permutations)	Uses stacks and queues to solve real-world problems.
17	Deque (Double-Ended Queue)	Sequences and patterns	Builds on queues to handle bidirectional data structures.
18	Advanced Stack Problems	Graph theory (DFS)	Uses stacks to solve graph traversal problems.
19	Advanced Queue Problems	Graph theory (BFS)	Uses queues to solve graph traversal problems.
20	Final Project	Problem-solving	Integrates all stack and queue concepts into a single project.

Trees and Graphs

S.No	Topic	Math Concept	Connection to Previous Topic
21	Introduction to Trees	Hierarchical relationships	Builds on linked lists to handle hierarchical data structures.
22	Tree Traversals	Sequences and patterns	Uses trees to handle data traversal.
23	Binary Search Trees (BST)	Sorting and searching	Builds on trees to handle sorted data structures.
24	Balanced Trees (AVL)	Balancing algorithms	Uses BSTs to handle balanced data structures.
25	Heaps	Sorting and ordering	Builds on trees to handle priority-based data structures.
26	Heap Operations	Sequences and series	Uses heaps to solve sorting problems.
27	Introduction to Graphs	Graph theory (nodes and edges)	Builds on trees to handle networked data structures.
28	Graph Traversals	Graph theory (DFS, BFS)	Uses graphs to solve traversal problems.
29	Shortest Path Algorithms	Graph theory (Dijkstra’s algorithm)	Builds on graphs to solve optimization problems.
30	Minimum Spanning Tree (MST)	Graph theory (Kruskal’s algorithm)	Uses graphs to solve network optimization problems.
31	Advanced Graph Problems	Graph theory (topological sorting)	Builds on graphs to solve dependency-based problems.
32	Final Project	Problem-solving	Integrates all tree and graph concepts into a single project.

Advanced DSA

S.No	Topic	Math Concept	Connection to Previous Topic
33	Dynamic Programming (DP)	Sequences and series (Fibonacci)	Builds on recursion to optimize solutions.
34	DP Problems	Combinatorics (knapsack)	Uses DP to solve optimization problems.
35	Greedy Algorithms	Optimization	Builds on DP to solve optimization problems.
36	Backtracking	Combinatorics (permutations)	Uses recursion to solve combinatorial problems.
37	Divide and Conquer	Sorting and searching	Builds on recursion to solve sorting problems.
38	Segment Trees	Number theory (range queries)	Uses trees to handle range-based problems.
39	Advanced Algorithms	Graph theory (network flow)	Builds on graphs to solve network optimization problems.
40	Final Project	Problem-solving	Integrates all advanced DSA concepts into a single project.

Advanced Topics and Problem-Solving

S.No	Topic	Math Concept	Connection to Previous Topic
41	Trie Data Structure	String matching	Builds on trees to handle string-based problems.
42	Disjoint Set Union (DSU)	Graph theory (connected components)	Uses graphs to solve connectivity problems.
43	Advanced DP Problems	Combinatorics (subset sum)	Builds on DP to solve advanced optimization problems.
44	Bit Manipulation	Binary numbers, bitwise operations	Uses loops and logic to solve problems efficiently at the bit level.
45	Advanced Graph Algorithms	Graph theory (Floyd-Warshall)	Builds on graphs to solve advanced optimization problems.
46	String Algorithms	Pattern matching	Uses strings to solve pattern-matching problems.
47	Advanced Backtracking	Combinatorics (N-Queens)	Builds on backtracking to solve complex combinatorial problems.
48	Advanced Greedy Algorithms	Optimization (activity selection)	Uses greedy algorithms to solve scheduling problems.
49	Final Project	Problem-solving	Integrates all advanced DSA concepts into a single project.
50	Revision and Practice	Problem-solving	Reinforces all concepts learned so far.

Competitive Programming Preparation

S.No	Topic	Math Concept	Connection to Previous Topic
51	Number Theory	Prime numbers, modular arithmetic	Builds on loops and math logic to solve number-based problems.
52	Combinatorics	Permutations, combinations	Uses recursion and math logic to solve counting problems.
53	Game Theory	Probability and decision-making	Builds on recursion and DP to solve game-based problems.
54	Computational Geometry	Geometry (polygons, circles)	Uses math logic and DSA to solve geometry problems.
55	Advanced Algorithms	Polynomials, FFT	Builds on DSA and math to solve complex algorithmic problems.
56	Code Galatta Practice	Problem-solving	Reinforces all concepts learned so far.
57	Mock Contests	Problem-solving	Simulates real competitive programming contests.
58	Interview Preparation	Problem-solving	Prepares for technical interviews.
59	Revision and Practice	Problem-solving	Reinforces all concepts learned so far.
60	Final Project	Problem-solving	Integrates all advanced DSA concepts into a single project.

C Language

Module 1: Introduction and First Program

- Why Programming
- History of C Language
- Hello World Program

Module 2: Variables and Data types

- Identifiers in C
- Variables and DataTypes
- Constants

Module 3: Console IO Operations

- Printf and Scanf
- Unformatted IO Functions

Module 4: Operators and Expressions

- Expressions and Arithmetic Operators
- Relational and Logical Operators
- Bitwise Operators

Module 5: Control Flow Statements

- If Statement
- Switch Statement
- Unconditional Branching using goto statement
- While Loop
- Do While Loop
- For Loop
- Break and Continue
- Special Cases

Module 6: Working with Functions

- Introduction and Writing Functions
- Scope of Variables, Storage Classes, Pass by Value and reference
- Recursion

Module 7: Working with Arrays

- Arrays Declaration and Initialization
- Sample Programs using Arrays
- Arrays as Function Parameters
- 2-Dimensional Array

Module 8: Pointers

- Introduction to Pointers
- Pointers as Function Parameter
- Pointer Arithmetic
- Pointers and Arrays
- Function Pointers
- Dynamic Memory Allocation using malloc
- calloc and comparision with malloc

Module 9: String Handling

- Introduction to Strings
- Sample Program
- More Sample Programs
- Standard String Library Functions
- Array of String

Module 10: Structures and Unions

- Declaring and Instantiating Structures
- Structure as Parameter and Pointer to Structure
- Enumerated Data Type
- Union
- Bit Fields

Module 11: File Handling

- What is a Stream
- File Handling-Writing and Reading Characters
- Writing and Reading Structure in Text Format
- Writing and Reading in Binary Format

Module 12: Pre-Processor Directives

- Understanding Pre-Processor directives
- Header Files and Project

Module 13: Command Line Arguments and Variable Arguments

1. Command Line Argument

C++ Language Syllabus

Module 1:- Introduction and First Program

- First C++ Program

Module 2:- Language Features

- How C++ differs from C
- Variables Declaration
- Function overloading
- Optional Parameters
- Reference Variables
- Operator overloading
- Basics of Console Input and Output
- Constant Pointers
- Dynamic Memory Allocation

Module 3:- OOPs Concepts

- Overview of OOPs Principles
- Introduction to classes & objects
- Creation & destruction of objects
- Data Members
- Member Functions
- this Pointer
- Constructor &Destructor
- Static class member
- Friend class and functions
- Namespace

Module 4:-- Inheritance

- Introduction and benefits
- Access Specifier
- Base and Derived class Constructors
- Types of Inheritance
- Down casting and up casting
- Function overriding
- Virtual functions
- Destructor overriding

Module 5:- Polymorphism

-What is Polymorphism
-Pure virtual functions
-Virtual Base Class

Module 6:- I/O Streams

-C++ Class Hierarchy
-File Stream
-Text File Handling
-Binary File Handling
-Error handling during file operations
-Overloading << and >> operators

Module 7:- Exception Handling

-Introduction to Exception
-Benefits of Exception handling
-Try and catch block
-Throw statement
-Pre-defined exceptions in C++
-Writing custom Exception class
-Stack Unwinding

Module 8:-- Templates

-Introduction
-Function Templates
-Class Templates

CORE JAVA

Module 1: Java Language Environment

- Object Oriented
- Platform Independent
- Automatic Memory Management
- Compiled / Interpreted approach
- Robust
- Secure
- Dynamic Linking
- Multi-Threaded
- Built-in Networking

Model 2: Java Fundamentals

- Data types
- Operators
- Control Statements
- Arrays
- Enhanced for-loop
- Enumerated types,
- Static import
- Auto boxing
- C-style formatted I/O
- Variable arguments

Module 3: Essentials of Object-Oriented Programming

- Object and Class Definition
- Using encapsulation to combine methods and data in a single class
- Inheritance and Polymorphism

Module 4: Writing Java Classes

- Encapsulation
- Polymorphism
- Inheritance
- OOP in Java
- Class Fundamentals
- Using Objects
- Constructor
- Garbage Collection
- Method Overloading
- Method Overriding
- Static Members
- Understanding Interface
- Using Interfaces

Module 5: Packages

- Why packages
- Understanding Class path
- Access modifiers & their Scope

Module 6: Exception Handling

- When an exception occurs
- Importance of Exception Handling
- Exception Propagation
- Exception Types
- Using try and catch
- throw, throws, finally
- Writing User defined Exceptions

Module 7: I/O Operations in Java

- Byte Oriented Streams
- File Handling
- Readers and Writers

Module 8: Multithreaded Programming

- Introduction to Multi-Threading
- Understanding Threads & its States
- Java Threading Model
- Thread class & Runnable Interface
- Thread Priorities
- Thread Synchronization
- Interthread Communication
- Preventing Deadlocks

Module 9: Java Util Package / Collections Framework

- Collection & Iterator Interface
- Enumeration
- List and ArrayList
- Vector
- Comparator
- Set Interface & SortedSet
- Hashtable
- Properties

Module 10: Generics

- Introduction to Generics
- Using Built-in Generics Collections
- Writing Simple Generic Class
- Bounded Generics
- Wild Card Generics

Module 11: Abstract Window Toolkit

- Graphics
- Color and Font
- AWT Components/Controls
- Event Handling & Layouts

Module 12: Swing Programming

- Introduction to Swing & MVC Architecture
- Light Weight Component
- Swing Hierarchy
- Atomic Components e.g. JButton, JList and more
- Intermediate Container e.g. JPanel, JSplitPane and more
- Top-Level Container e.g. JFrame and JApplet
- Swing Related Events

DATA SCIENCE USING PYTHON SYLLABUS

Module 1: DATA SCIENCE & PYTHON INTRODUCTION

-Python Introduction
-Installation
-Variables
-Data types
-Operators
-Input
-Comments

Module 2: LOOPS

-If statements
-If..else statements
-While loop
-For Loops

Module 3: FUNCTIONS

-Basic math
-Advanced Mathematical Operators
-Creating your own functions
-Defining functions in python
-Advanced Math function creation

Module 4: DATA STRUCTURE OPERATIONS

Array

-Accessing Array
-Slicing
-Insert
-Modify
-Pop
-Scalar
-Vector
-0D,1D,2D,3D,4D,5D

List

-Len
-Append
-Insert
-Clear
-Del
-Remove
-Pop
-Index
-Count
-Sort
-Reverse
-Concatenation
-Type
-In and not in statement
-Replication
-List function

Tuples

-Len
-Concatenation
-Tuple
-Count
-Index
-Accessing using array
-Negative indexing with different ranges
-Replication

Sets

-Add
-Update
-Remove
-Clear
-Len
-Del
-Union
-Intersection
-Difference
-Discard
-Pop() with no arguments
-Set()
-Issubset()

Dictionaries

-Len
-Adding new key value
-Pop
-Popitem
-Del
-Clear
-Copy
-Items
-Values
-Keys
-Dict

Module 5: FILE HANDLING

File Operations

-Open()
-Read()
-Read by passing values()
-Readline()
-Write()
-Append()
-Remove()
-Close()
-Access mode
-Buffering

Read Files

-Create Files
-Delete Files
-Writing Files

Module 6: TYPE CONVERSION

-Int to str
-Int to float
-Str to float

Module 7: FUNCTIONAL PROGRAMMING

-Map
-Filter
-Lambda

Module 8: MODULES & LIBRARIES

Functions,Modules and standard libraries

-System version
-Getcwd
-System platform
-Datetime
-Components of datetime
-Time

Numpy

-0D,1D,2D,3D
-Ndim
-Version
-Ndimn
-Dtype
-Int
-Float
-Complex
-i1,i2,i4
-arange
-Numpy Zeros
-Numpy ones

Creating Array Indexing

-2D indexing
-3D indexing
-Negative indexing

Creating Array Slicing

-Using parameter
-Using colon
-Using 2D
-Using 3D

Array shape & Reshaping

-Shape
-Flattening numpy array into specific shape
-Reshape

Module 9: DATA VISUALIZATION USING PYTHON

-Matplotlib Introduction
-Matplotlib Plotters
-Matplotlib Bar Plotters
-Matplotlib Scatters
-Two different scatters
-Matplotlib Grids & Bars
-Seaborn point plotters

Module 10: Pandas

-Introduction
-Pandas version
-Series
-Series data creation
-Series creation with custom index
-Head
-Tail
-Mean
-Sum
-Type
-Sort_values
-Dataframes
-Rename
-Reset index
-Drop columns and row
-Ascending

Module 11: OpenCV

-RGB image
-Gray scale image
-RGB to grayscale conversion
-Imread
-Imwrite
-Imshow
-Imreadcolor
-Imgshape
-Imgresize
-BGRTORGB
-Image(Rowshape,columnshape)
-Reshape array (3D to 2D)

Module 12: Counters

-Mostcommon()
-Mostcommon(Using Slicing)
-Mostcommon(Using negative indexing)
-Zip()
-Barchart using Counters

Module 13: Processing Functions

-Rand
-randInt
-linspace
-rand with parameters
-seed
-uniform
-random.random
-arrange
-argmax

Module 14: Installing packages

-Pip install
-Pip list

Module 15: OOPS Concept

Classes

-Creation
-_init_ constructor
-Self

Objects

-Attributes
-Methods
-Modify object
-Delete object with attribute
-Delete object
-Accessing object with attributes
-Object Methods
-Object Method call

Inheritance

-Parent class creation
-Child class
-Accessing parent class from child class

Encapsulation

-Data hiding
-Public method
-Mangling method
-Access specifiers
-Public
-Private
-Protected

Polymorphism

Operator overloading

Module 16: Statistics

-Mean
-Median
-Mode
-Variance
-Standard deviation

Module 17: ADVANCED DATA STRUCTURES IN PYTHON

-List
-Tuples
-Set
-Dictionary
-Counter

Module 18: ADVANCED DATA FRAMES(USING REAL DATASET)

-Dataframes in Python Using Real Time Dataset
-Dataset Description using dataframes
-Loading Dataset
-Display Records of Dataframes
-Value Counts and Cross Tabulation
-Sorting Dataframes
-Creating New Columns
-Grouping and Aggregating
-Joining Dataframes
-Filtering Records

Module 19: CLUSTERING (USING REAL DATASET)

-Clustering
-How Clustering works
-Finding Similarities Using Distances
-Euclidean Distance
-Cosine Similarity
-K-Means Clustering
-Plotting with Segments
-Cluster Centers

Module 20: FORECASTING (USING REAL DATASET)

-Forecasting Overview
-Components of Time-Series Data
-Moving Average
1.Loading and visualizing the TimeSeries Dataset
2.Forecasting using Moving Average

Module 21: ADVANCED COMPUTER VISION TECHNIQUES

-Invariant Transformation
-Grayscale contrast and stretching
-Bilateral Filtering
-Thresholding
-Contours

Data Structure Syllabus

MODULE 1: Introduction

-Data structures introduction
-Algorithms introduction
-Asymptomatic analysis
-Overview of Pointers, Structure
-Overview of Class and Objects

MODULE 2: Introduction to Arrays

-One dimensional Array and operations
-Two dimensional Array and operations

MODULE 3: Introduction to Linked list

-Singly linked list
-Doubly linked list
-Circular linked list

MODULE 4: Stack introduction

-Array implementation of stack
-Linked list implementation of stack

MODULE 5: Queue introduction

-Array representation
-Linked list representation
-Circular Queue
-Priority Queue

MODULE 6: Tree introduction

-Binary Tree
-Binary search tree
-AVL tree
-B and B+ tree

MODULE 7: Graph introduction

-Implementation of graph
-BFS and DFS
-Spanning tree

MODULE 8: Searching introduction

-Linear search
-Binary search

MODULE 9: Sorting introduction

-Bubble sort
-Merge sort
-Quick sort
-Heap sort

MODULE 10: Miscellaneous

-Hash Table

DATABASE MANAGEMENT SYSTEM SYLLABUS

Module 1: Introduction

-DBMS Introduction | Set 1
-DBMS Introduction | Set 2 (3-Tier Architecture)
-DBMS Architecture 2-level 3-level
-Need For DBMS
-Data Abstraction and Data Independence
-Database Objects
-Multimedia Database
-Interfaces
-Categories of End Users
-Use of DBMS in System Software
-Choice of DBMS | Economic factors
-Disadvantages of DBMS

Module 2: Entity Relationship Model

-ER Model
-Enhanced ER Model
-Minimization of ER Diagram
-ER Model: Generalization, Specialization and Aggregation
-Recursive Relationships
-Impedance Mismatch

Module 3: Relational Model

-Relational Model and CODD Rules
-Relational Model
-Keys in Relational Model (Candidate, Super, Primary, Alternate and Foreign)
-Number of possible Superkeys
-Anomalies in Relational Model
-Mapping from ER Model to Relational Model
-Strategies for Schema design
-Schema Integration
-Star Schema in Data Warehouse modeling
-Data Warehouse Modeling |Snowflake Schema
-Dimensional Data Modeling

Module 4: Relational Algebra

-Introduction
-Basic Operators
-Extended Operators
-Inner Join vs Outer Join
-Join operation Vs nested query
-DBMS | Tupple Relational Calculus
-Row oriented vs. column oriented data stores
-How to solve Relational Algebra Problems for GATE
-How to Solve Relational Algebra Problems for GATE

Module 5: Functional Dependencies

-Functional Dependency and Attribute Closure
-Finding Attribute Closure and Candidate Keys using Functional Dependencies
-Armstrong’s Axioms in Functional Dependency
-Equivalence of Functional Dependencies
-Canonical Cover

Module 6: Normalization

-Introduction
-Normal Forms
-Minimum relations satisfying 1NF
-The Problem of redundancy in Database
-Dependency Preserving Decomposition
-Lossless Join Decomposition
-Loss Less Join and Dependency Preserving Decomposition
-How to find the Highest Normal Form of a Relation
-Domain Key normal form
-Introduction of 4th and 5th Normal form
-De-normalization in Databases
-DBMS | Data Replication

Module 7: Transactions and Concurrency Control

-Introduction
-ACID Properties
-Concurrency Control -Introduction
-Implementation of Locking in DBMS
-Concurrency Control Protocols – Lock Based Protocol
-Concurrency Control Protocol | Graph Based Protocol
-Concurrency Control Protocol | Two Phase Locking (2-PL)-I
-Concurrency Control Protocol | Two Phase Locking (2-PL)-II
-Concurrency Control Protocol | Two Phase Locking (2-PL)-III
-Concurrency Control Protocol | Multiple Granularity Locking
-Concurrency Control Protocol | Thomas Write Rule
-Concurrency Control | Polygraph to check View Serializabilty
-DBMS | Log based recovery
-Timestamp Ordering Protocols
-Introduction to Time-Stamp and Deadlock Prevention Schemes
-Dirty read in SQL
-Types of Schedules
-Conflict Serializability
-View Serializability
-How to test if two schedules are View Equal or not ?
-Recoverability of Schedules
-Precedence Graph for testing Conflict Serializabilty
-Transaction Isolation Levels in DBMS
-Database Recovery Techniques
-Starvation in DBMS
-Deadlock in DBMS
-DBMS | OLAP vs OLTP
-Types of OLAP Systems
-DBMS | Types of Recoverability of Schedules and easiest way to test schedule | Set 2
-Web Information Retrieval | Vector Space Model
-Why recovery is needed?

Module 8: Indexing, B and B+ trees

-Indexing and its Types
-B-Tree | Set 1 (Introduction)
-B-Tree | Set 2 (Insert)
-B-Tree | Set 3 (Delete)
-B+ Tree (Introduction)
-Bitmap Indexing
-Inverted Index
-Difference between Inverted Index and Forward Index
-SQL queries on clustered and non-clustered Indexes

Module 9: File Organization

-File Organization – Set 1
-File Organization – Set 2 (Hashing in DBMS)
-File Organization – Set 3
-File Organization – Set 4

Module 10: Advanced Topics

-RAID
-Query Optimization
-How to store a password in database?
-Storage Area Networks
-Network attached storage
-Data Warehousing
-Data Warehouse Architecture
-Characteristics and Functions of Data warehouse
-Difficulties of Implementing Data Warehouses
-Data Mining

Module 11: SQL Tutorial

-SQL Practicals

COMPUTER ARCHITECTURE SYLLABUS

Module 1: Basic Computer Instructions

- A simple understanding of Computer
- Issues in Computer Design
- Computer System Level Hierarchy
- Computer Architecture and Computer Organization
- Basic Computer Instructions
- Timing diagram of MOV Instruction in Microprocessor
- Assembly language and High level language
- Addressing Modes
- Memory based Vs Register based addressing modes
- Von Neumann architecture
- Harvard Architecture
- Interaction of a Program with Hardware
- Simplified Instructional Computer (SIC)
- Instruction Set used in simplified instructional Computer (SIC)
- Instruction Set used in SIC/XE
- RISC and CISC
- RISC and CISC | Set 2
- Vector processor classification
- Essential Registers for Instruction Execution
- Single Accumulator based CPU organization
- Stack based CPU Organization
- General Register based CPU Organization
- Data Transfer instructions in AVR microcontroller
- Arithmetic instructions in AVR microcontroller
- Conditional Branch Instructions in AVR Microcontroller
- CALL Instructions and Stack in AVR Microcontroller
- Branch Instructions in AVR Microcontroller
- Logical Instructions in AVR Microcontroller
- Data Manipulation Instructions
- Machine Control Instruction
- Very Long Instruction Word (VLIW) Architecture

Module 2: Instruction Design and Format

- Different Instruction Cycles
- Essential Registers for Instruction Execution
- Machine Instructions
- Instruction Formats (Zero, One, Two and Three Address Instruction)
- 2-address instruction and 1-address instructions
- 3-address instruction and 0-address instruction
- 3-address instruction and 2-address instructions
- Register content and Flag status after Instructions
- Debugging a machine level program
- Vector Instruction Format
- Vector instruction types
- Branch Prediction in Pentium
- Instruction Word Size
- Problem Solving on Instruction Format

Module 3: Computer Arithmetic

- Computer Arithmetic | ALU and Data Path
- Computer Arithmetic | Set 1
- Computer Arithmetic | Set 2
- Difference between 1’s complement and 2’s complement
- Restoring Division Algorithm For Unsigned Integer
- Non-Restoring Division For Unsigned Integer
- Booth’s Algorithm
- Overflow in Arithmetic Addition
- How the negative numbers are stored in memory?
- Conventional Computing vs Quantum Computing

Module 4: Microprogrammed Control

- Micro-Operation
- Microarchitecture and Instruction Set Architecture
- Types of Program Control Instructions
- Difference between CALL and JUMP instructions
- Hardwired v/s Micro-programmed Control Unit
- Implementation of Micro Instructions Sequencer
- Performance of Computer
- Control Unit and design
- Horizontal micro-programmed Vs Vertical micro-programmed control unit
- Comparisons between Hardwired Vs Micro-programmed Control unit
- Computer Organization | Subprogram and its characteristics

Module 5: Memory Organization

- Introduction to memory and memory units
- Memory Hierarchy Design and its Characteristics
- Difference between Byte Addressable Memory and Word Addressable Memory
- Difference between Simultaneous and Hierarchical Access Memory Organisations
- Register Allocation
- Cache Memory
- Cache Organization | Set 1 (Introduction)
- Multilevel Cache Organization
- Locality and Cache friendly code
- Locality of Reference and Cache Operation
- Amdahl’s law and its proof
- Subroutine, Subroutine nesting and Stack memory
- RAM vs ROM
- What’s difference between CPU Cache and TLB?
- Different Types of RAM
- Types of computer memory (RAM and ROM)
- Secondary memory – Hard disk drive
- Introduction to solid-state drive (SSD)
- Read and Write operations in memory
- 2D and 2.5D Memory organization

Module 6: Input and Output Systems

- Priority Interrupts | (S/W Polling and Daisy Chaining)
- I/O Interface (Interrupt and DMA Mode)
- Direct memory access with DMA controller 8257/8237
- Asynchronous input output synchronization
- Programmable peripheral interface 8255
- Interface 8255 with 8085 microprocessor for 1’s and 2’s complement of a number
- 8255 (programmable peripheral interface)
- Microcomputer system
- Working of 8085-based Single board microcomputer
- Interface 8254 PIT with 8085 microprocessor
- Synchronous Data Transfer
- Input-Output Processor
- MPU Communication
- Memory mapped I/O and Isolated I/O
- BUS Arbitration

Module 7: Pipelining

- Instruction Level Parallelism
- Execution, Stages and Throughput
- Types and Stalling
- Dependencies and Data Hazard

Module 8: Electronics Part

- Microprocessor
- Microprocessor | Externally Initiated Operations
- Bus organization of 8085 microprocessor
- Generations of computer
- Intel x86 evolution and main features
- Memory Banking
- Introduction to quantum computing
- Conventional Computing vs Quantum Computing
- Rethinking binary with Quantum computers
- Flynn’s taxonomy
- Clusters In Computer Organisation
- Parallel processing – systolic arrays
- 8259 PIC Microprocessor
- Block Diagram of 8259 Microprocessor
- Microprocessor | 8251 USART
- Evolution of Microprocessors
- Human – Computer interaction through the ages
- Computer Ports
- Introduction to Parallel Computing
- Hardware architecture (parallel computing)
- Computer Architecture | Multiprocessor and Multicomputer
- Timing diagram of INR M

Module 9: Programs

- Program for Binary To Decimal Conversion
- Program for Decimal to Binary Conversion
- Program for decimal to octal conversion
- Program for octal to decimal conversion
- Program for hexadecimal to decimal

OPERATING SYSTEM SYLLABUS

Module 1: Introduction

- What is an Operating System
- Simple Batch Systems
- Multi-programmed Batches systems
- Time-Sharing Systems
- Personal-computer systems
- Parallel systems
- Distributed Systems
- Real-Time Systems
- OS – A Resource Manager

Module 2: Memory Organization & Management

- Memory Organization
- Memory Hierarchy
- Memory Management Strategies
- Contiguous versus non- Contiguous memory allocation
- Partition Management Techniques
- Logical versus Physical Address space
- Swapping
- Paging
- Segmentation
- Segmentation with Paging

Module 3: Virtual Memory

- Demand Paging
- Page Replacement
- Page-replacement Algorithms
- Performance of Demand Paging
- Thrashing
- Demand Segmentation and Overlay Concepts

Module 4: Processes

- Introduction
- Process states
- process management
- Interrupts

Module 5: Inter process Communication Threads

- Introduction
- Thread states
- Thread Operation
- Threading Models.

Module 6: Processor Scheduling

- Scheduling levels
- pre-emptive vs no pre-emptive scheduling
- Priorities
- scheduling objective
- scheduling criteria
- scheduling algorithms
- demand scheduling
- real-time scheduling

Module 7: Process Synchronization

- Mutual exclusion
- software solution to Mutual exclusion problem
- hardware solution to Mutual exclusion problem
- Semaphores
- Critical section problems
- Case study on Dining philosopher problem, Barbershop problem etc.

Module 8: Deadlocks

- Introduction of deadlock
- resource concepts
- necessary conditions for deadlock
- deadlock solution, deadlock prevention
- deadlock avoidance with Bankers algorithms
- deadlock detection
- deadlock recovery

Module 9: Device Management

- Disk Scheduling Strategies
- Rotational Optimization
- System Consideration
- Caching and Buffering

Module 10: File System

- Introduction
- File Organization
- Logical File System
- Physical File System
- File Allocation strategy
- Free Space Management
- File Access Control, Data Access Techniques
- Data Integrity Protection
- Case study on file system viz FAT32, NTFS, Ext2/Ext3 etc.

Module 11: I/O Systems

- Kernel I/O Subsystem
- Disk Structure
- Disk Scheduling
- Disk Management
- Swap Space Management
- RAID Structure
- Case study on Linux System
- Case study on Windows XP.