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 C and C++ 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
Frequently Asked Questions
This course is designed to help learners master Python programming, one of the most versatile and beginner-friendly languages used in data science, web development, automation, and AI.
It is ideal for students, beginners, and professionals who want to start their programming journey or strengthen their coding foundation with Python.
The course runs for 4 months, combining live interactive sessions, coding practice, and mini projects for real-world learning.
The total course fee is ₹5,000, which includes live classes, study materials, practical assignments, and certification upon completion.
You’ll learn Python fundamentals, including variables, data types, loops, functions, file handling, object-oriented programming, and working with libraries like NumPy and Pandas.
No prior coding experience is required. The course starts from scratch and gradually progresses to intermediate and advanced concepts.
You’ll work on hands-on projects such as calculator apps, data analysis tasks, and small automation scripts to build real-world coding skills.
Upon completion, you’ll receive an industry-recognized Python Programming Certificate from HITMI, validating your technical knowledge and coding ability.
We also provide career and placement guidance, helping you prepare for developer roles or advanced learning paths like AI, data science, and web development.
Enrollment is open through our official HITMI website or by visiting our training center, where our team will guide you with registration and batch details.
