Programming in Python Course
Start your journey into the world of programming and problem-solving with our expertly designed Python course. From learning Python fundamentals and writing clean, readable code to mastering object-oriented programming, advanced data structures, and algorithms, you’ll gain the skills needed to solve real-world problems efficiently. Through hands-on coding exercises, projects, and interview-focused challenges, this program prepares you to excel in competitive programming, crack technical interviews, and build a strong foundation for a successful career in software development, data science, AI, and emerging technologies.
4 Months
.Duration
Virtual Live
Classes
100% Job
Assurance
Languages
English | Hindi
Course Highlights
Master Core Programming:
Build a strong foundation with Java fundamentals.
Data Structures & Algorithms (DSA)
Learn arrays, linked lists, stacks, queues, trees, graphs, hashing, heaps, and more.
Problem-Solving Skills:
Solve 300+ coding challenges and real-world problems.
Master Core Python Concepts
Variables, loops, functions, error handling, and modules.
Master these Tools
Skills Covered
Time & Space Complexity Analysis
.
Competitive Programming Techniques
.
Debugging & Optimization
.
Coding Interview Readiness
.
Data Structures
.
Course Curriculum
Build strong foundations in Java, master Data Structures & Algorithms, sharpen problem-solving skills, and prepare for top tech interviews with projects & real-world practice.
Module 1: Introduction to Python & Setup
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Why Python? History, Features & Industry Use Cases
Installing Python 3.x (Windows/Mac/Linux)
Installing & Setting up VS Code, PyCharm, Jupyter Notebook
Understanding Python Shell, IDLE & Virtual Environments
Writing & Running Your First Program
Understanding Python Execution Model
Python Keywords & Identifiers
Comments & Docstrings
Understanding PEP 8 (Python Style Guide)
Module 2: Python Basics & Core Syntax
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Variables, Data Types & Memory Management
Numbers (int, float, complex) & Type Casting
Strings – Slicing, Concatenation, Formatting (f-strings, .format())
String Built-in Methods (complete list)
Input & Output Functions
Operators – Arithmetic, Assignment, Comparison, Logical, Bitwise, Identity, Membership
Boolean Logic & Truthy/Falsy Values
Control Flow: if, else, elif, Nested Conditions
Loops: for, while, break, continue, else with loops
Iterators & Iterables
range(), enumerate(), zip()
Mini Coding Exercises
Module 3: Data Structures & Collections
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Introduction to DSA
• What is DSA & Why it Matters
• Time Complexity & Space Complexity
• Big-O, Big-Ω, Big-Θ Notations
• Analyzing Algorithms (Best, Worst, Average Case)
• Recursion Basics & Recurrence Relations
Arrays & Strings
• 1D & 2D Arrays in Python
• Common Array Operations: Traversal, Insertion, Deletion, Searching
• Sliding Window Technique
• Prefix Sum & Kadane’s Algorithm
• String Operations & Problems (Palindrome, Substrings, Pattern Matching)
Linked Lists
• Singly Linked List – Creation, Insertion, Deletion, Traversal
• Doubly Linked List – Forward/Backward Traversal
• Circular Linked List
• Reverse a Linked List (Iterative & Recursive)
• Detect Loop in a Linked List (Floyd’s Cycle Detection)
Stacks & Queues
• Implement Stack (List & collections.deque)
• Implement Queue (List, deque, queue.Queue)
• Circular Queue & Priority Queue (heapq)
• Problems: Balanced Parentheses, Next Greater Element
• Deque – Double Ended Queue Implementation
Hashing & Dictionaries
• Hash Tables & Hash Functions
• Collision Handling (Chaining & Open Addressing concepts)
• Use of Python Dictionary & collections.Counter for hashing problems
• Problems: Two-Sum, Subarray Sum Equals K, Frequency Counting
Trees
• Binary Tree Basics: Traversals (Inorder, Preorder, Postorder)
• Binary Search Tree (BST): Insertion, Deletion, Search
• Lowest Common Ancestor (LCA)
• Height, Diameter, Balanced Tree
• Level Order Traversal (BFS)
• Problems: Symmetric Tree, Path Sum, Serialize/Deserialize Tree
Heaps & Priority Queues
• Min-Heap & Max-Heap (heapq module)
• Heap Operations: push, pop, heapify
• Top-K Problems (Top K Elements, Kth Largest Element)
• Heap Sort Implementation
Graphs
• Graph Representation (Adjacency List, Matrix)
• BFS & DFS Traversals
• Shortest Path Algorithms: Dijkstra’s, Bellman-Ford
• Minimum Spanning Tree: Kruskal’s & Prim’s Algorithm
• Detecting Cycles (Directed & Undirected Graphs)
• Topological Sorting
• Connected Components
Advanced Topics
Dynamic Programming (DP)
• Introduction to DP & Memoization
• Fibonacci (Recursive, Memoized, Tabulation)
• Knapsack Problems (0/1, Unbounded)
• Longest Common Subsequence (LCS), Longest Increasing Subsequence (LIS)
• Matrix DP (Minimum Path Sum, Unique Paths)
Greedy Algorithms
• Activity Selection Problem
• Huffman Coding
Backtracking
• N-Queens Problem
• Rat in a Maze
• Word Search
Bit Manipulation
• Bitwise Operators Tricks
• Count Set Bits, Find Single Number
Advanced Data Structures (Optional for Deep Learners)
• Disjoint Set Union (Union-Find)
• Segment Tree / Fenwick Tree (Binary Indexed Tree)
• Trie (Prefix Tree)
Module 4: Functions & Functional Programming
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Defining & Calling Functions
Function Parameters – Positional, Keyword, Default, *args, **kwargs
Return Values & Multiple Returns
Recursion & Tail Recursion Optimization
Lambda Functions
Map, Filter, Reduce
Closures & Decorators (Function Wrappers)
First-Class Functions
Docstrings & Type Hints
Creating Your Own Modules & Importing
name == "main" idiom
Module 5: Object-Oriented Programming (OOP)
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Classes & Objects
Attributes vs. Instance Variables
Constructors (init) & Destructors (del)
Class & Static Methods
Encapsulation, Inheritance, Polymorphism, Abstraction
Method Overriding & Overloading (Pythonic way)
Multiple Inheritance & MRO (Method Resolution Order)
Dunder/Magic Methods (str, repr, len, add, etc.)
Private & Protected Members
Dataclasses (Python 3.7+)
Real-World OOP Projects
Module 6: File Handling & Working with Data
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Working with Text Files (Read, Write, Append, with open())
Working with Binary Files
CSV Files – csv module, Reading/Writing
JSON Files – json module, Serialization/Deserialization
Pickling & Unpickling Objects
Directory & File Management (os, shutil, glob, pathlib)
Handling Large Files & Streaming Data
Module 7: Exception Handling & Debugging
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try, except, else, finally
Raising Exceptions (raise)
Custom Exceptions & Exception Hierarchy
Logging with logging module
Using assert Statements
Debugging with pdb
Module 8: Python Standard Libraries (Deep Dive)
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math, random, statistics, fractions, decimal
datetime, calendar, time
itertools (Combinations, Permutations, Infinite Iterators)
functools (caching, partial functions, reduce)
os, sys, shutil, platform
subprocess (Running System Commands)
typing (Static Type Hints)
re (Regular Expressions – Complete Coverage)
Module 9: Python for Data Handling & Visualization
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NumPy – Arrays, Vectorization, Broadcasting
Pandas – Series, DataFrames, Indexing, GroupBy
Data Cleaning & Manipulation
Matplotlib – Line, Bar, Scatter, Pie Charts
Seaborn – Statistical Visualizations
Hands-On Data Mini-Projects
Module 10: Automation & Web Scraping
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Automating Files, Folders, and Emails
Using requests for HTTP
Web Scraping with BeautifulSoup & lxml
Handling APIs & JSON Data
Automating Excel with openpyxl
Creating CLI Tools
Module 11: Concurrency & Advanced Python
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Iterators & Generators (Deep Dive)
Context Managers (with Statement & Custom Context Managers)
Multithreading, Multiprocessing, AsyncIO
Performance Optimization & Profiling
Memory Management & Garbage Collection
Design Patterns in Python (Singleton, Factory, Observer)
Module 12: Algorithms & Problem-Solving
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Big-O Notation (Time/Space Complexity)
Searching – Linear, Binary, Hash-Based
Sorting – Bubble, Merge, Quick, Heap
Recursion & Dynamic Programming (Fibonacci, Knapsack)
Graph Algorithms (DFS, BFS, Dijkstra)
Competitive Programming Problems
Module 13: Testing, Debugging & Deployment
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Unit Testing with unittest & pytest
Test-Driven Development (TDD) Basics
Code Linting & Formatting (pylint, black)
Packaging Your Code (setuptools, pip)
Publishing to PyPI
Virtual Environments & Dependency Management
About Programming in Python Course
Step into the world of programming and automation with our Programming in Python course. This program is designed to take you from a complete beginner to a confident Python programmer, ready to build real-world projects and solve problems using Python.
What You’ll Learn:
✅ Core Python Mastery – Variables, data types, functions, conditionals, loops, and Python syntax
✅ Object-Oriented Programming (OOP) – Classes, objects, inheritance, polymorphism, and encapsulation
✅ File Handling & Automation – Read/write files, work with CSV/JSON, and create automation scripts
✅ Modules & Packages – Learn to use and create reusable Python modules
✅ Error Handling & Debugging – Exception handling, logging, and debugging best practices
✅ Libraries & APIs – Introduction to Python libraries like requests, os, math, and working with REST APIs
✅ Web Scraping Basics – Use BeautifulSoup and requests to extract data from websites
✅ Virtual Environments & pip – Manage dependencies like a pro
✅ Project Building – Hands-on projects like a calculator, weather app, file organizer, and basic web scraper
✅ Version Control & Collaboration – Learn Git & GitHub for modern software development workflows
Why Choose This Course?
🎯 Hands-On Learning – Practical exercises and mini-projects after every module
🚀 Industry-Relevant Curriculum – Focus on Python for scripting, automation, and real-world applications
💡 Expert Mentorship – Learn from experienced Python developers and industry professionals
📈 Career-Ready Skills – Build a strong foundation for roles in automation, scripting, backend development, or further learning (AI/ML, Data Science)
Career Opportunities After the Course
List potential roles students can pursue after completing the course, such as
- Python Developer
- Automation Engineer
- Algorithm Expert / Problem Solver
- Technical Interview Preparation / Coding Mentor
With 100% job assurance, our course prepares you for a lucrative career in Coding.
Authorised Training Partners
Live Virtual Classes
Batch Timings
📅 Weekday Batches
🕖 Monday to Friday | 7:00PM – 9:00PM
📅 Weekend Special Batches
🕖 Saturday | 4:00 PM – 9:00 PM
🕖 Sunday | 10:00 AM – 3:00 PM
Total Course Duration : 4 Months