Course description

This 16-lecture course is designed to provide a solid foundation in Python programming and an introduction to Generative AI. Tailored for beginners, the course includes both theoretical lessons and hands-on projects to ensure that learners can apply their knowledge in real-world scenarios. The entire course is more of a story telling format to beginners in realtime. The recordings can give you an immersive experience in class.

Lecture 1: Introduction to Generative AI and Python

  • Overview of the course structure and objectives.

  • Introduction to Python and its importance in AI.

  • Overview of Generative AI, including its applications and relevance in today’s world.

Python Fundamentals (Lectures 2–10)

Lecture 2: Introduction to Python Basics

  • Overview of programming and Python as a language.

  • Setting up and using Google Colab for coding.

  • Exploring GitHub for code storage and collaboration.

  • Basic syntax in Python: print statements, comments.

Lecture 3: Variables and Data Types

  • Understanding variables and their role in programming.

  • Exploring different data types: integers, floats, strings.

  • Simple input and output operations using input() and print() functions.

Lecture 4: Control Structures

  • Conditional statements: if, elif, else.

  • Comparison and logical operators.

  • Introduction to loops: while loops and their use in repetitive tasks.

Lecture 5: Lists and For Loops

  • Lists: creation, indexing, slicing, and basic list methods.

  • Introduction to for loops and their applications in iterating through lists.

Lecture 6: Sets and Loops

  • Working with sets: creation and methods.

  • Continuation of for loops, applied to sets and other data structures.

Lecture 7: Tuples and Dictionaries

  • Overview of tuples: creation and properties.

  • Working with dictionaries: creation, accessing values, and basic dictionary methods.

Lecture 8: Functions in Python

  • Understanding and using built-in functions.

  • Defining custom functions, parameters, and return values.

Lecture 9: Modules and Libraries

  • Introduction to Python modules and libraries.

  • Using the math module and understanding Python packages.

  • Introduction to PIP for managing Python libraries.

Lecture 10: String Operations and File Handling

  • String operations and formatting.

  • Reading from and writing to files using Google Colab’s file system.

  • Hands-on project: Create a simple Python project to demonstrate understanding of Python fundamentals.

Introduction to Generative AI (Lectures 11–13)

Lecture 11-12: Text Generation and LLMs

  • Overview of text generation tools and Large Language Models (LLMs) like ChatGPT, Gemini, and Claude.

  • Hands-on exercises using OpenAI Playground and Google AI Studio for text generation.

  • Practical comparison of outputs from different AI tools.

Lecture 13: AI-driven Code Generation and Prompt Engineering

  • Introduction to AI-based code generation using tools like ChatGPT and Claude.

  • Understanding Cursor IDE for AI-assisted coding.

  • Practical project: Build a simple web page using AI-generated code.

Advanced Generative AI Concepts (Lectures 14–16)

Lecture 14: Image Generation and Running LLMs Locally

  • Overview of image generation tools such as DALL-E, Midjourney, and Stable Diffusion.

  • Practical exercise: Generating and animating images using runwayML.

  • Running open-source LLMs locally using tools like Ollama and LMStudio.

Lecture 15: Retrieval Augmented Generation (RAG)

  • Using LLMs with custom data through RAG techniques.

  • Introduction to embeddings and vector stores (chromaDB, qdrant).

  • Practical exercise: Building a RAG pipeline to process and store PDFs in qdrant cloud.

Lecture 16: Building Real AI Projects

  • Introduction to Langchain and LlamaIndex.

  • Hands-on project: Create a RAG-based question-answering system on a webpage.

  • Exploring the open-source AI ecosystem and next steps for continued learning.

By the end of the course, learners will have gained a thorough understanding of Python programming and practical experience with Generative AI, enabling them to build AI-driven projects.

What will i learn?

  • 1. Proficiency in Python Programming: Mastery of Python fundamentals, including variables, data types, loops, conditionals, functions, and error handling. The ability to write efficient, readable, and maintainable Python code. Confidence in using Python for general-purpose programming and problem-solving tasks.
  • 2. Understanding of Object-Oriented Programming (OOP): Knowledge of object-oriented programming concepts such as classes, objects, inheritance, polymorphism, and encapsulation. Ability to implement OOP principles in Python to build modular and scalable applications.
  • 3. Introduction to Artificial Intelligence (AI): A clear understanding of what AI is, its applications, and how it impacts industries. The ability to grasp basic AI concepts such as machine learning, neural networks, and data-driven decision-making.
  • 4. Hands-On Experience with AI Tools and Libraries: Practical experience using Python libraries like NumPy (for numerical computing), Pandas (for data manipulation), Matplotlib (for data visualization), and Scikit-learn (for machine learning). Ability to use these libraries to build and manipulate datasets, visualize data, and implement machine learning algorithms.

Requirements

  • >>Prerequisites: No Prior Programming Experience Required: This course is designed specifically for beginners, so no prior programming or AI experience is needed. It will start from the basics and gradually build up to more advanced concepts. Basic Computer Skills: A basic understanding of how to navigate a computer (such as installing software and using applications) is necessary. Willingness to Learn: A passion for learning programming and artificial intelligence is key! This course requires dedication and a willingness to follow along with coding exercises and mini-projects.
  • >>Hardware Requirements: Computer with Internet Access: You’ll need a computer with internet access to download tools, access course materials, and work on assignments. The course is fully online, so reliable internet is essential.
  • >>Software Requirements: Python: You will need to install Python (latest version recommended: Python 3.x). Python is free to download and use. Integrated Development Environment (IDE): You’ll need an IDE to write and execute your Python code. Recommended IDEs are: VS Code (Visual Studio Code) – Free and highly popular for Python development. PyCharm – Another excellent Python IDE with a free version. Alternatively, you can use any code editor of your choice, but these two are recommended due to their Python-specific features. Python Libraries: Throughout the course, you'll be using libraries like: NumPy for numerical operations Pandas for data manipulation Matplotlib for data visualization Scikit-learn for machine learning Instructions for installing these libraries will be provided during the course.

Frequently asked question

This course is designed for absolute beginners who have no prior experience with Python or Artificial Intelligence (AI). It’s perfect for individuals who want to start their journey in programming and AI, including those looking to switch careers or enhance their skill set.

No prior programming experience is required. The course is structured for beginners, so you’ll be guided step by step. A basic understanding of computers and the ability to follow instructions will be enough to get started.

You will need a computer with internet access to access the course materials. Additionally, you'll need to install: Python: The latest version of Python (Python 3.x). IDE (Integrated Development Environment): We recommend using either VS Code or PyCharm for writing and running Python code. Libraries: You’ll also learn how to install and use libraries like NumPy, Pandas, Matplotlib, and Scikit-learn (installation instructions will be provided).

No prior knowledge of AI or machine learning is required. This course is meant to introduce you to these concepts from the ground up, providing a solid foundation for beginners.

₹599

₹1499

Lectures

19

Skill level

Beginner

Expiry period

Lifetime

Certificate

Yes

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