C & Data Structure, Python, Aptitude, Group Discussion and HR

Course Module for C, Data Structures and Algorithms training:

Module 1: Introduction and First Program

• Why Programming?
• History of C Language
• Hello World Program

Module 2: Variables and Datatypes

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

Module 7: Pointers

• Introduction to Pointers
• Pointers as Function Parameter
• Pointer Arithmetic
• Pointers and Arrays
• Function Pointers
• Dynamic Memory Allocation using malloc
• Calloc and comparison with malloc

Module 8: String Handling

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

Module 9: Structures and Unions

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

Module 10: 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 11: Pre-Processor Directives

• Understanding Pre-Processor directives
• Header Files and Project

Module 12: Command Line Arguments and Variable Arguments

• Command Line Argument
• Variable Number of Arguments

Module 13: Introduction to Data Structures and Algorithms

• Variables, Data Types, Data Structures and Abstract Data Types (ADTs)
• What’s an algorithm?
• Analysis of algorithm and its goal
• Running Time Analysis
• Asymptotic Notations (ϴ, O, Ώ, o, ⍵)
• Master’s Theorem for Divide and Conquer Recurrences, Subtract and Conquer Recurrences
• Method of Guessing and Confirming
• Amortized Analysis

Module 14: Recursion and Backtracking

• What is Recursion? Why recursion?
• Format of a Recursive Function
• Recursion and Memory (Visualization)
• Recursion versus Iteration
• What is Backtracking? Example Algorithms of Backtracking

Module 15: Linked Lists

• What is a Linked List? Linked List as an ADT
• Comparison between Linked List and Array
• Singly Linked Lists
• Doubly Linked Lists and Memory-efficient Doubly Linked List
• Circular Linked Lists
• Unrolled Linked Lists
• Skip Lists

Module 16: Stacks and Queues

• What is a Stack? Stack as an ADT
• Implementation of a Stack
• What is a Queue? Queue as an ADT
• Implementation of a Queue

Module 17: Trees

• What is a Tree?
• Binary Trees: Types and Properties
• Binary Tree Traversals
• Generic Trees (N-ary Trees)
• Threaded Binary Tree Traversals (Stack or Queue-less Traversals)
• Expression Trees
• XOR Trees
• Binary Search Trees (BSTs)
• Balanced Binary Search Trees
• AVL (Adelson-Velskii and Landis) Trees
• Red-Black Trees
• Splay Trees
• B-Trees
• Augmented Trees
• Interval Trees [Segment Trees]
• Scapegoat Trees

Module 18: Priority Queues and Heaps

• What is a Priority Queue? Priority Queue ADT
• Priority Queue Applications and Implementations
• Heaps and Binary Heaps
• Binary Heaps
• Heapsort

Module 19: Disjoint Sets ADT

• Introduction
• Equivalence Relations and Equivalence Classes
• Disjoint Sets ADT and Applications
• Tradeoffs in Implementing Disjoint Sets ADT
• Fast UNION Implementation (Slow FIND and Quick FIND)

Module 20: Graph Algorithms

• Introduction
• Applications of Graphs
• Graph Representation
• Graph Traversals
• Topological Sort
• Shortest Path Algorithms
• Minimal Spanning Tree

Module 21: Sorting

• What is Sorting? Why is it necessary?
• Classifications of Sorting Algorithms
• Various sorting algorithms: Bubble, Selection, Insertion, Shell, Merge, Heap, Quick, Tree, Counting, Bucket, Radix and Topological

Module 22: Searching

• What is Searching? Why is it necessary?
• Types of searching?
• Unordered Linear Search
• Sorted/Ordered Linear Search
• Binary Search
• Interpolation Search
• Comparing Basic Searching Algorithms
• Symbol Tables and Hashing
• String Searching Algorithms

Course Module for Python training:

Module 1:

• Features of Python
• Using the Python Interpreter
  • Invoking the Interpreter
  • The Interpreter and Its Environment
• Introduction to Anaconda
  • Anaconda Navigator
  • Anaconda Prompt
  • IPython Console
  • Jupyter qt-console
  • Jupyter Notebook
  • Spyder
• An Informal Introduction to Python
  • Using Python as a Calculator
  • First Steps Towards Programming
• Control Flow Tools
  • if Statements
  • for Statements
  • The range() Function
  • break and continue Statements, and else Clauses on Loops
  • pass Statements
  • Defining Functions
  • More on Defining Function
  • Function special attributes
  • Coding Style

Module 2:

• Data Structures
  • Lists
  • The del statement
  • Tuples and Sequences
  • Sets
  • Dictionaries
  • Looping Techniques
  • More on Conditions
  • Comparing Sequences and Other Types

Module 3:

• Concept of Modules
  • Standard Modules
  • The dir() Function
  • Packages
• Input and Output
  • Fancier Output Formatting
  • Reading and Writing Files

Module 4:

• Object: properties and operations
• Class as a blueprint for objects
• Fields: Python convention for defining private fields
• Constructors: overloading and chaining
• Designing static properties, operations and blocks in Python
• Special method names in a class and their uses (e.g. __new__, __del__, __str__ etc)

Module 5:

• Single and multiple inheritances
• Method overriding and polymorphism
• Iterators
• Generators
• Generator Expressions
• Errors and Exceptions
• Syntax Errors
• Exceptions
• Handling Exceptions
• Raising Exceptions
• User-defined Exceptions
• Defining Clean-up Actions
• Predefined Clean-up Actions

Aptitude Course – 10 sessions

GD- 5 classes

HR- 10 classes