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PYTHON PROGRAMMING COURSE

The Python programming course provides learners with a strong foundation in one of the most widely used programming languages. It begins with an introduction to Python, covering its syntax, data types, and core concepts. Participants are guided through essential programming structures such as variables, operators, conditional statements, loops, and functions. 

The course also emphasizes working with data by exploring lists, tuples, dictionaries, sets, and file handling. As learners progress, they gain skills in object-oriented programming, error handling, and modules. More advanced topics include working with libraries for data analysis, visualization, and automation, as well as developing simple applications. By the end of the course, participants will be able to write clean, efficient Python code, solve real-world problems, and build a foundation for specialized areas such as web development, data science, and machine learning.

Led by experienced trainers who are also industry professionals, our course offers personalized mentorship and attention to help you gain a deep understanding of all the essential concepts and skills. Starting from the basics, our curriculum is tailored to prepare you for the real-world challenges of industry. 

Upon completion, you will receive a professional certificate that will enhance your resume and open up better job opportunities. Join us at the best Python institute in Hyderabad to kickstart your career in full stack development!

COURSE ENTRY REQUIREMENT

Basic Entry Requirements (Beginner Level)

  • No prior programming experience required (most beginner Python courses start from scratch).
  • Basic computer literacy – ability to use a computer, install software, and navigate files/folders.
  • High school level mathematics – understanding of logic, numbers, and simple algebra is helpful.
  • Device requirement – a laptop or desktop computer with internet access.

Intermediate/Advanced Python Courses

  • Prior knowledge of Python basics (variables, loops, functions, data types, etc.).
  • Understanding of problem-solving and algorithms.
  • Familiarity with basic programming concepts in any language (for learners transitioning from Java, C, or JavaScript).
  • For specialized tracks (e.g., Python for Data Science, Machine Learning, or Web Development):
    • Some knowledge of statistics and mathematics (for data-focused courses).
    • Familiarity with HTML/CSS/JavaScript (for web development with Python).

COURSE SYLLABUS

 Beginner to Advance Level

Module 1: Introduction to Python
  • History & features of Python
  • Installing Python & IDEs (PyCharm, VS Code, Jupyter)
  • Python interactive shell & script execution
  • Python syntax, keywords, identifiers
  • Input/output & comments
Module 2: Python Basics
  • Variables & data types (numbers, strings, booleans)
  • Type conversion & casting
  • Operators (arithmetic, relational, logical, bitwise, assignment, identity, membership)
  • String operations, slicing, formatting, f-strings
Module 3: Control Flow
  • Conditional statements (if, elif, else)
  • Loops (for, while)
  • break, continue, pass
  • Iterators & generators
Module 4: Data Structures
  • Lists: indexing, slicing, methods
  • Tuples: immutable sequences
  • Sets: union, intersection, difference
  • Dictionaries: keys, values, methods
  • Nested collections
Module 5: Functions
  • Defining & calling functions
  • Arguments (positional, keyword, default, variable-length)
  • Scope (local, global, nonlocal)
  • Lambda functions
  • Recursion
  • Decorators & higher-order functions
Module 6: Modules & Packages
  • Importing modules (math, random, os, sys, etc.)
  • Creating custom modules
  • Virtual environments & pip
  • Package management
Module 7: File Handling
  • Opening, reading, writing files
  • File modes & file objects
  • Handling CSV, JSON, and XML files
  • Context managers (with)
Module 8: Exception Handling
  • Errors vs exceptions
  • try, except, finally
  • Raising exceptions
  • Custom exceptions
Module 9: Object-Oriented Programming (OOP)
  • Classes & objects
  • Attributes & methods
  • Inheritance (single, multiple, multilevel)
  • Polymorphism
  • Encapsulation & abstraction
  • Dunder methods (__init__, __str__, etc.)
Module 10: Advanced Python
  • Iterators & generators
  • List comprehensions, dict/set comprehensions
  • Closures
  • Regular expressions (re module)
  • Python memory management & garbage collection
Module 11: Python Libraries for Development
  • NumPy – numerical computing
  • Pandas – data manipulation & analysis
  • Matplotlib / Seaborn – data visualization
  • Requests – working with APIs
  • SQLite3 – database handling
Module 12: Python for Web Development
  • Introduction to Flask / Django
  • Building REST APIs
  • Templates & routing
  • Basic CRUD applications
Module 13: Python for Data Science & Automation
  • Data analysis with Pandas
  • Web scraping (BeautifulSoup, Selenium)
  • Automation with Python scripts
  • Intro to Machine Learning (scikit-learn basics)
Module 14: Testing & Debugging
  • Debugging with pdb
  • Unit testing (unittest, pytest)
  • Logging in Python
Module 15: Capstone Projects
  • Calculator & To-do app
  • Web scraper
  • REST API with Flask
  • Data analysis project with Pandas
  • Automation script (e.g., email sender, file organizer)
Python Programming Course for Beginners to Advanced with Real Projects

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