Hello , myself Venkata Bhamidipati  from India.A dynamic telecom architect with over 20 years engineering experience in integration , maintenance,installation ,protocol testing.  Currently I am working as freelancer  ,role- Machine learning training.  I have also served my role as a technical architect , test manager and technical solution architect. worked as a a technical lead and junior technical officer in BSNL for more than 10 years.  And I take coding classes for the interested students like machine learning, python .

Degree: Bachelors of Science - University: Andhra university

Degree:

Designing a comprehensive course on Python involves covering the basics of programming, Python language features, various libraries and frameworks, and real-world applications.

• Learning Objectives:

  Week 1-2: Introduction to Programming and Python Basics

  1. Introduction to Programming
  2. Getting Started with Python
  3. Control Flow and Functions

   

  Week 3-4: Data Structures in Python

  1. Lists and Tuples
  2. Dictionaries and Sets
  3. String Manipulation

   

  Week 5-6: Object-Oriented Programming (OOP) in Python

  1. Introduction to OOP
  2. Advanced OOP Concepts
  3. Exception Handling

  Week 7-8: File Handling and Modules

  1. Working with Files
  2. Modules and Packages
  3. Virtual Environments

   

  Week 9-10: Python Web Development Basics

  1. Introduction to Web Development
  2. Flask Framework
  3. RESTful APIs with Flask

   

  Week 11-12: Data Science and Machine Learning with Python

  1. Introduction to Data Science
  2. Introduction to Machine Learning
  3. Final Project: Real-World Application
• Course Outline:

  Week 1-2: Introduction to Programming and Python Basics

  1. Introduction to Programming
     • Understanding algorithms and problem-solving
     • Basics of computer memory and CPU
  2. Getting Started with Python
     • Installing Python and setting up a development environment
     • Basic syntax, variables, and data types
     • Input and output operations
  3. Control Flow and Functions
     • Conditional statements (if, elif, else)
     • Loops (for, while)
     • Functions and modular programming

  Week 3-4: Data Structures in Python

  1. Lists and Tuples
     • Understanding lists and tuples
     • List comprehensions
     • Common list operations
  2. Dictionaries and Sets
     • Working with dictionaries and sets
     • Iterating through dictionaries
     • Use cases for sets
  3. String Manipulation
     • String methods and formatting
     • Regular expressions in Python
     • String handling techniques

  Week 5-6: Object-Oriented Programming (OOP) in Python

  1. Introduction to OOP
     • Understanding classes and objects
     • Encapsulation, inheritance, and polymorphism
     • Creating and using classes in Python
  2. Advanced OOP Concepts
     • Abstraction and interfaces
     • Class methods and static methods
     • Multiple inheritance
  3. Exception Handling
     • Handling exceptions with try, except, finally
     • Custom exception classes
     • Best practices for error handling

  Week 7-8: File Handling and Modules

  1. Working with Files
     • Reading and writing text files
     • CSV and JSON file handling
     • Binary file operations
  2. Modules and Packages
     • Creating and importing modules
     • Understanding the Python Standard Library
     • Introduction to package management (pip)
  3. Virtual Environments
     • Creating and managing virtual environments
     • Isolating project dependencies
     • Using requirements.txt

  Week 9-10: Python Web Development Basics

  1. Introduction to Web Development
     • Overview of web technologies
     • Basics of HTML, CSS, and JavaScript
  2. Flask Framework
     • Setting up a Flask project
     • Routing and templates
     • Handling forms and user input
  3. RESTful APIs with Flask
     • Designing RESTful APIs
     • Implementing CRUD operations
     • Testing APIs with tools like Postman

  Week 11-12: Data Science and Machine Learning with Python

  1. Introduction to Data Science
     • Basics of data analysis with Pandas
     • Data visualization with Matplotlib and Seaborn
  2. Introduction to Machine Learning
     • Overview of machine learning concepts
     • Using scikit-learn for simple machine learning tasks
  3. Final Project: Real-World Application
     • Students will work on a final project that integrates various concepts learned throughout the course. This could be a web application, a data analysis project, or a small machine learning application.
• Recomended Audience:

  This Hobby classes and Extra curricular activities are suitable for students whose age is more than or equal to 5 years old. As your child continues to grow, you will notice new and exciting abilities that your child develops. A child’s brain grows the most during the first five years of life. By age 5, the brain has reached approximately 90 percent of its adult size. This means that much of the brain’s structure and function has been established. Hence our best recommended audience for these hobbies classes are all students who are minimum 5 years old and more. Even a grownup students upto 16 years old can also go ahead for these Hobbies & Extra Curricular classes with their learning.

• Pre-Requisite Requirement:

  For attending Hobbies and Extra curricular activities classes, Basic pre-requisite requirement is having interest in learning of that class. Without having natural interest on particular topic/class, it's not meaningful to proceed with it alongwith Instructors. So it's advisable to have these as a part of your learning phase of your life if you are really inclined and motivated to learn that hobby or activity. You should have all the items and required things with you at your home which are needed in that class. If not then you must buy from market it after taking suggestion from Instructors as per provided standard.

• Course Level:
  Beginner
• Language of Teaching:
  English
• Class Schedule Availiability:
  Morning