5-session intensive · Beginner friendly · Hands-on

LEARN
PYTHON
Easily.

Go from "I've never written code" to building and deploying a simple Python web app with guidance — and laying the exact foundation needed for AI agent development — in 5 focused sessions.

Python Streamlit Git & GitHub Data Structures Functions Error Handling
Apply for next cohort → View curriculum ↓
5
Live sessions
7.5hrs
Total instruction
1
Deployed web app
5+
Coding assignments
0
Prior experience needed
→ Variables & Data Types → Functions → Lists & Dictionaries → Loops & Conditionals → Error Handling → Git & GitHub → Streamlit → Cloud Deployment → Operators → Tuples & Sets → Exception Handling → Session State → Secrets Management → Variables & Data Types → Functions → Lists & Dictionaries → Loops & Conditionals → Error Handling → Git & GitHub → Streamlit → Cloud Deployment → Operators → Tuples & Sets → Exception Handling → Session State → Secrets Management
Why learn Python

One of the world's
most influential programming languages.

Python is the #1 language for AI, data science, automation, and web backends. Python is increasingly becoming a core skill across AI, automation, data, and software engineering roles.

🌍
Most in-demand language
Python has topped the TIOBE and Stack Overflow developer surveys for years. It's the first language listed in the majority of AI, data, and backend engineering job descriptions.
🧠
Foundation for every AI framework
LangChain, LangGraph, Google ADK, OpenAI SDK, Hugging Face Transformers — they are all Python-first. Python is the most widely used language for modern AI agent development and is the primary language used in most AI frameworks.
⚡
Fast to learn, deep to master
Python's readable syntax means you write working code in your first session. But it has the depth to power everything from scripts to distributed systems at Google scale.
📦
Massive ecosystem
Over 500,000 packages on PyPI. Whatever you need — data manipulation, web apps, machine learning, automation — someone has already written a Python library for it.
🚀
Deploy and Share project
With Streamlit, you can turn any Python script into a shareable web app in minutes. No web development experience required — if you can write Python, you can ship a product.
🎯
The right entry point
This course is explicitly designed as the prerequisite for our AI Agents course. Every concept taught — functions, data structures, Git — maps directly to what you'll use when building agents.
Curriculum

5 sessions.
5 building blocks.

Each session is 1.5 hours — split between focused concept delivery and hands-on coding. Every session includes Hands-on Programming examples and Assignments to practice.

Session 1 Intro to Python
Installation & Setup Syntax rules & indentation Adding comments Variables & Data Types Programming examples & assignments
Session 2 Operators & Loops
Arithmetic Operators Comparison Operators Logical Operators Python Loops Programming examples & assignments
Session 3 Conditionals & Data Structures
Conditional Statements Lists & Tuples Dictionaries & Sets Programming examples & assignments
Session 4 Functions, Errors & Git
Python Functions Error & Exception Handling Basic Git & GitHub workflows Core Git commands Programming examples & assignments
Session 5 Streamlit & Deployment
Intro to Streamlit Install Streamlit library Build the Streamlit project Deploy to Streamlit Community Cloud Session State & Secrets Management Programming examples & assignments
What you'll build

Code that runs.
Live on the internet.

Every session produces a working Python script pushed to GitHub. The course ends with a real web app deployed publicly to Streamlit Community Cloud.

Session 5 Capstone
Deployed Streamlit Web App
A fully deployed, publicly accessible web application built entirely in Python. You choose the idea — a data dashboard, a quiz app, a personal portfolio tool — then build it with Streamlit, manage secrets securely, handle session state, and deploy it live on Streamlit Community Cloud with a shareable URL.
Python Streamlit Streamlit Community Cloud Session State Secrets Management GitHub
Sessions 1–2
Python scripting foundations
Write Python scripts that store and manipulate data, perform arithmetic, compare values, and loop through collections. Understand exactly why indentation is syntax and how Python evaluates expressions.
Python Variables Operators Loops
Session 3
Data structure programs
Build programs that store, filter, and transform collections of data using lists, tuples, dictionaries, and sets — the same structures that power every AI agent's memory and tool output parsing.
Lists & Tuples Dictionaries Sets Conditionals
Session 4
Versioned project on GitHub
Write reusable Python functions with proper error handling, then push the project to GitHub using real Git workflows — init, add, commit, push, branching. Your codebase is version-controlled from day one.
Functions Try / Except Git CLI GitHub
Python + AI Agents

Every concept here
shows up in agent code.

This course isn't a standalone Python course — it's the engineered prerequisite for our AI Agents programme. Here's exactly how each topic maps to real agent development work.

🗂️
Dictionaries → Tool outputs & agent state
Every LangChain tool returns a dictionary. LangGraph's StateGraph stores agent memory as a typed dictionary. You cannot read agent outputs without fluency in Python dicts.
⚙️
Functions → Agent tools
In LangChain, an agent tool is just a Python function decorated with @tool. Every tool you'll build in the AI Agents course is a Python function with typed arguments and a return value.
🔁
Loops → Agent reasoning cycles
The ReAct loop (Think → Act → Observe → Repeat) is a while loop in Python. The LangGraph StateGraph is a graph traversal. Loops are not just basics — they are the agent's heartbeat.
🛡️
Error handling → Resilient agents
Production agents wrap every tool call in try/except. When an API fails, the agent needs to recover gracefully — not crash. Exception handling is how you build agents that survive real-world usage.
🔀
Git & GitHub → Team collaboration & deployment
Most professional AI agent projects use Git and GitHub for collaboration and deployment. LangSmith CI, Streamlit deployment, and Vertex AI pipelines all pull from Git. Version control is not optional — it is infrastructure.
🖥️
Streamlit → Agent front-ends
The capstone Data Analyst AI Agent in our Build AI Agents course uses Streamlit for its chat interface and file upload UI. You will use the exact same Streamlit patterns you learn here.
The stack

Tools you'll use.
Tools that matter.

Python 3
The language itself — syntax, data types, control flow, functions, and standard library
Streamlit
Turn Python scripts into shareable web apps — the same library used in the AI Agents capstone
Git
Version control from the command line — init, commit, branch, merge, push, and pull
GitHub
Host your projects, collaborate with others, and deploy your Streamlit app directly from a repo
Streamlit Cloud
Free hosting for Streamlit apps — deploy in minutes with a public URL from your GitHub repo
VS Code
Industry-standard code editor with Python extension, linting, and integrated terminal
pip & venv
Install packages and isolate project environments — the foundation of every Python project setup
Python REPL
Interactive shell for testing expressions and exploring data structures in real time
Learning outcomes

What you'll be able
to do after.

✓
Write clean, readable Python scripts using proper syntax, indentation, and comments — the same conventions used in production codebases
✓
Confidently use all core data structures — lists, tuples, dictionaries, and sets — to store, query, and transform data programmatically
✓
Write reusable functions with arguments and return values, and handle errors gracefully with try/except blocks
✓
Control program flow with loops and conditionals — for/while loops, if/elif/else chains, and logical operator combinations
✓
Manage a project with Git and GitHub — version control, commits, branches, and pushing code to a remote repository
✓
Build and deploy a Streamlit web app to Streamlit Community Cloud with a public URL — a real project you can share with anyone
✓
Manage session state and secrets in Streamlit — building apps that remember user interactions and keep API keys secure
✓
Build the Python foundation required to confidently begin the Build AI Agents course.
Who it's for

Starting from
absolute zero.

No prior coding experience is needed. If you can use a computer and you're curious about Python, you're ready. This course meets you where you are.

🎓
Students & freshers
  • Any undergraduate or postgraduate discipline
  • No prior programming experience required
  • Want a real technical skill on the resume
  • Planning to join the AI Agents course next
  • Prefer learning by doing, not by watching
💼
Non-technical professionals
  • Working in business, ops, finance, or marketing
  • Curious about AI but don't know where to start
  • Want to automate repetitive tasks with Python
  • Need to understand what engineers are building
  • Want to transition toward more technical roles
🔄
Career changers
  • Background outside of software or IT
  • Looking to enter AI, data, or tech roles
  • Need a structured starting point — not tutorials
  • Want something deployable for the portfolio
  • Planning to continue into the AI Agents track

Highly skilled trainers, very knowledgeable and supportive. It was a wonderful learning experience. Would highly recommend for anyone looking for internships or learning opportunities.

Abhishek Abhi

I had a great experience as a Full-Stack Intern, where I gained hands-on experience in full-stack development. I worked on real-time projects that challenged me and helped improve my skills. The teammates were very supportive and always ready to help, making the learning experience even more valuable.

Omprava Prusty

The training program covered a wide range of topics, starting from the basics and gradually progressing to more advanced concepts. I would like to express my gratitude to Raghu sir, who played a pivotal role in my learning journey. consistently demonstrated the qualities of an excellent mentor.

Shantha A H
Format & schedule

Focused.
Practical. Fast.

Session structure
Total sessions5 sessions
Session duration1.5 hours
Theory per session~45 min
Hands-on per session~45 min
Total instruction7.5 hours
Assignments1 per session + capstone
Prerequisites & delivery
Prior coding experienceNot required
Python prior knowledgeNot required
Delivery modeIn-person / hybrid
Capstone submissionGitHub + live URL
CertificateYes — on completion
Next stepBuild AI Agents course
Your instructor

Taught by someone
who builds this.

👨‍💻
Python Faculty
Course Designer · Practitioner

This course is designed and delivered by a practitioner who writes Python daily — not just an instructor, but someone who actively uses Python in real-world projects. The curriculum is built backwards from what AI and data engineering roles actually require, so every concept you learn has a clear reason to exist.

Every example in the course was written specifically for learners who are starting from zero. No assumed knowledge, no skipped steps, no "I'll leave that as an exercise." You leave every session with code that actually runs.

Python Streamlit Git & GitHub AI Agent Development Production Systems

Your first line
won't write itself.

5 sessions. 7.5 hours. One deployed web app and the Python foundation to build anything next — including AI agents.

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