Jumpstart Python & Gen AI: Zero to Hero for Beginners
- Description
- Curriculum
- FAQ
- Reviews
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
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Overview of the course structure and objectives.
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Introduction to Python and its importance in AI.
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Overview of Generative AI, including its applications and relevance in today’s world.
Python Fundamentals (Lectures 2–10)
Lecture 2: Introduction to Python Basics
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Overview of programming and Python as a language.
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Setting up and using Google Colab for coding.
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Exploring GitHub for code storage and collaboration.
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Basic syntax in Python: print statements, comments.
Lecture 3: Variables and Data Types
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Understanding variables and their role in programming.
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Exploring different data types: integers, floats, strings.
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Simple input and output operations using input() and print() functions.
Lecture 4: Control Structures
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Conditional statements: if, elif, else.
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Comparison and logical operators.
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Introduction to loops: while loops and their use in repetitive tasks.
Lecture 5: Lists and For Loops
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Lists: creation, indexing, slicing, and basic list methods.
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Introduction to for loops and their applications in iterating through lists.
Lecture 6: Sets and Loops
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Working with sets: creation and methods.
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Continuation of for loops, applied to sets and other data structures.
Lecture 7: Tuples and Dictionaries
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Overview of tuples: creation and properties.
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Working with dictionaries: creation, accessing values, and basic dictionary methods.
Lecture 8: Functions in Python
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Understanding and using built-in functions.
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Defining custom functions, parameters, and return values.
Lecture 9: Modules and Libraries
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Introduction to Python modules and libraries.
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Using the math module and understanding Python packages.
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Introduction to PIP for managing Python libraries.
Lecture 10: String Operations and File Handling
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String operations and formatting.
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Reading from and writing to files using Google Colab’s file system.
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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
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Overview of text generation tools and Large Language Models (LLMs) like ChatGPT, Gemini, and Claude.
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Hands-on exercises using OpenAI Playground and Google AI Studio for text generation.
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Practical comparison of outputs from different AI tools.
Lecture 13: AI-driven Code Generation and Prompt Engineering
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Introduction to AI-based code generation using tools like ChatGPT and Claude.
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Understanding Cursor IDE for AI-assisted coding.
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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
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Overview of image generation tools such as DALL-E, Midjourney, and Stable Diffusion.
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Practical exercise: Generating and animating images using runwayML.
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Running open-source LLMs locally using tools like Ollama and LMStudio.
Lecture 15: Retrieval Augmented Generation (RAG)
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Using LLMs with custom data through RAG techniques.
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Introduction to embeddings and vector stores (chromaDB, qdrant).
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Practical exercise: Building a RAG pipeline to process and store PDFs in qdrant cloud.
Lecture 16: Building Real AI Projects
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Introduction to Langchain and LlamaIndex.
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Hands-on project: Create a RAG-based question-answering system on a webpage.
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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.
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2
Introduction to Python- Introduction to programming and Python
- Overview of Google Colab
- Overview of Github
- Basic syntax: print statements, comments
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3
Introduction to Python - Contd..
- Variables and data types (integers, floats, strings)
- Simple input and output using `input()` and `print()`
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4
Control Structures
- Conditional statements (if, elif, else)
- Comparison and logical operators
- Introduction to loops (while loops)
- Using loops for repetitive tasks
– For loops can be understood on Day 5 class
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5
Data Structures
- Lists: creation, indexing, slicing
- Basic list methods (append, remove, etc.)
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6
Data Structures (contd..)
- Continue For loop after lists.
- Set Basics
- Set methods
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7
Data Structures (contd..)
- Tuples (Didnt add in syllabus) # Just gave an overview
- Dictionaries: creation, accessing values
- Basic dictionary methods
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8
Knowledge Check
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9
Functions
-Built-in Functions
-Defining and calling functions
- Parameters and return values
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10
Modules
- Introduction to modules and libraries
- Using the `math` module
- Introduction to Packages
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11
Libraries
- Packages continued..
- Understanding PIP
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12
Strings, Files, Python Project and Review of topics
- String operations and methods
- String formatting
- Reading from and writing to files using Colab's file system
- Basic file operations
- Review of all Python topics covered
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13
Knowledge Check 2
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14
Text Generation Tools and LLMs
- Overview of text generation tools
- LLMs - an Introduction
- Introduction to ChatGPT, Gemini and Claude
- Practical exercise: Comparing ChatGPT vs. Gemini (zero code exercise)
- Using OpenAI Playground and Google AI Studio
- Demo: Google AI Studio, Open AI Playground
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15
Text Generation Tools and LLMs - Contd
- Overview of text generation tools
- LLMs - an Introduction
- Introduction to ChatGPT, Gemini and Claude
- Practical exercise: Comparing ChatGPT vs. Gemini (zero code exercise)
- Using OpenAI Playground and Google AI Studio
- Demo: Google AI Studio, Open AI Playground
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16
Code Generation, Cursor IDE and Prompt Engineering
- Introduction to code generation with AI
- Leveraging Claude / ChatGPT to build tools / softwares
- Introduction to Cursor IDE
- Asking the right questions using better Prompt Engineering
- Practical Exercise : Utilize code generation capabilities and build a simple web page
