Python & Gen AI Basics: Transition from 0 to Hero in 15 days

Name: Python & Gen AI Basics: Transition from 0 to Hero in 15 days
Rating: 4.3 (78 reviews)

Unlock Python and Generative AI Basics in Just 15 Days

Created byArul Benjamin Chandru Ebenezer Vedanayagam

Last updated 11/2024

English

What you'll learn

Key comparisons between Java and Python: Syntax, variables, loops, and data structures
How to transition your Java skills to Python programming
Building Python projects with real-world applications
Fundamentals of Generative AI and how to apply them in everyday tasks
Practical coding challenges with a focus on Python’s simplicity compared to Java

Course content

6 sections • 15 lectures • 16h 48m total length

Introduction to Python58:32
- Introduction to programming and Python
- Overview of Google Colab
- Overview of Github
- Basic syntax: print statements, comments
Introduction to Python - Contd..1:05:02
- Variables and data types (integers, floats, strings)
- Simple input and output using `input()` and `print()`

Control Structures58:04
- Comparison and logical operators
- Conditional statements (if, elif, else)
- Introduction to loops (while loops)
- Using loops for repetitive tasks
– For loops can be understood on Day 4 class
Data Structures1:05:01
- Lists: creation, indexing, slicing
- Basic list methods (append, remove, etc.)
– Tuple introduction (W3 schools)
Data Structures (contd..)58:16
- Continue For loop after lists.
- Set Basics
- Set methods
- Dictionaries: creation, accessing values
- Basic dictionary methods

Text Generation Tools and LLMs1:11:09
- 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
Code Generation and Prompt Engineering1:12:50
- Introduction to code generation with AI
- Leveraging Claude / ChatGPT to build tools / softwares
- Asking the right questions using better Prompt Engineering
- Practical exercise: Building a python code generator using gemini AI model and fastAPI (Using AI code generation - zero code exercise) - Cursor IDE

Image Generation / recognition1:03:42
- Introduction to image generation tools
- Use cases for image generation tools
- Overview of tools: OpenAI DALL-E, Midjourney, Stable Diffusion 2
- Practical exercise: Generating image and animate it with runwayML (zero code exercise)
Running large language models (LLMs) locally1:06:34
- Introduction to open source LLMs
- Ollama Introduction
- Setting up Ollama and LM Studio for running the models locally
- Accessing local models with code
- Practical exercise: Creating a simple chatbot as like ChatGPT with Ollama and LMStudio (zero code exercise)
Retrieval Augmented Generation1:25:32
- RAG technique to use LLMs with our own Data
- Embeddings and vector stores (chromaDB, qdrant, pgvector)
- leveraging RAG to use our own data without exposing it to Model
- Practical exercise : python code exercise to build a RAG pipeline for chunking and storing the PDF in FAISS (Code to build the RAG system)
Langchain and LlamaIndex (LLM Frameworks)1:23:20
- Introduction to Langchain
- What is LlamaIndex and where to use it
- Practical exercise :
Build a question and answering system on a webpage with LlamaIndex and ChromaDB
Building real AI Projects54:12
- Chat with SQL using Langchain - My github project demo
- Open Source world of AI
- AI advanced : Next steps in learning

Requirements

Basic Java knowledge is helpful but not required. If you're familiar with Java, you'll appreciate the comparisons that make transitioning to Python easier.
No prior experience with Python or Generative AI is needed—we’ll cover everything from the ground up.
A computer with internet access to follow along and run Python code (preferably using Google Colab).
Curiosity and a willingness to learn Python and AI in a storytelling, engaging format!

Description

Curious about Python programming and Generative AI but not sure where to start? This 15-day beginner-friendly course is designed to take you from zero to confidently building AI-powered projects—all through a practical, storytelling approach! If you’re familiar with Java, we’ll make it even easier by comparing concepts between the two languages, helping you transition smoothly.

From mastering Python fundamentals to exploring popular AI tools like ChatGPT and DALL-E, this course covers everything you need to start working with AI without writing complex code. You’ll dive into hands-on exercises, learn to use local LLMs, and build real-world AI applications—all with no prior Python or AI experience required.

Course Outline:

Day 1-4: Python Fundamentals

Introduction to programming and Python
Overview of Google Colab and Github
Python syntax: print statements, comments, variables, and data types
Control structures: conditional statements, loops, and repetitive tasks
Data structures: lists, sets, tuples, and dictionaries

Day 5-7: Functions, Modules, and Packages

Defining and calling functions
Parameters and return values
Working with Python libraries and modules like math
Understanding PIP and how to install packages

Day 8: Files and Python Project

String operations and formatting
File handling: reading and writing files in Google Colab
A simple Python project based on the learner's understanding

Day 9-10: Introduction to Generative AI

Text generation tools and large language models (LLMs)
Practical exercises: Comparing ChatGPT and Gemini AI
Code generation with AI tools like Claude and ChatGPT
Prompt engineering for effective AI communication
Building a Python code generator using AI (no coding required)

Day 11-14: Advanced Generative AI Concepts

Image generation with tools like DALL-E, Midjourney, and Stable Diffusion
Running LLMs locally using Ollama and LM Studio
Retrieval Augmented Generation (RAG) technique with vector stores like ChromaDB
LLM frameworks: Langchain and LlamaIndex
Building a question-answering system using LLM frameworks

Day 15: Building Real AI Projects

Creating AI-powered tools like SQL chatbots using Langchain
Exploring the open-source world of AI and next steps in AI learning

By the end of the course, you’ll have a solid foundation in Python and Generative AI, with the confidence to build exciting AI projects. Perfect for curious minds looking to step into the future of tech!

Who this course is for:

Java programmers curious about learning Python quickly and efficiently
Beginners in Generative AI who want to explore its tools and applications
Educators and professionals seeking to apply AI to their work
Anyone who prefers a storytelling approach to learning with relatable, real-world examples

Python & Gen AI Basics: Transition from 0 to Hero in 15 days

What you'll learn

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Course content

Introduction2 lectures • 2hr 4min

Python - Control Structures and Data Structures3 lectures • 3hr 1min

Functions, modules and packages2 lectures • 2hr 10min

Files, Python Project and Review of topics1 lecture • 1hr 17min

Introduction to Generative AI2 lectures • 2hr 24min

Advanced Generative AI Concepts5 lectures • 5hr 53min

Requirements

Description

Who this course is for: