AI Accelerated Python Bootcamp: Learn Python in 8 Days

About Course

Build 6 real Python projects in 8 days, even if you’ve never written a line of code.

AI writes the first draft. You learn to read it line by line, fix it and make it better. By Day 8, your own script emails you a daily market brief like this one:

Daily market brief email built in the course

In the AI age, only fast learning makes sense

Learning to code used to be slow. You spent weeks on simple things before you could build anything useful, and many people lost steam and gave up. Not any longer.

In this course you learn just the basics first. Then you pick a real goal, get AI to draft the code, and learn exactly what you need to understand it, fix it and improve it. Every new concept comes with a reason to use it, so it sticks.

This course is for you if…

You’re a complete beginner who wants to learn Python quickly, without the boring parts
You want to automate real work: files, reports, emails and AI-powered tools
You’ve copied AI code before and want to finally understand it
You tried learning to code before and gave up because it was too slow

No coding experience needed. All you need is a Mac or Windows computer. Free versions of ChatGPT, Claude or Gemini work.

Start with foundations, then learn just in time

First you learn the core Python you need to read almost any script: types, functions, decisions, loops, lists and dictionaries, practised on real AI-written code. After that, each project brings in new skills at the moment you need them:

Your goal	What you learn just in time
Split expenses among friends	Python foundations, applied to a real script
Clean up a contact list	Reading and improving code line by line
Fix a broken script	Tracebacks, common errors, print and AI debugging, try/except
Organize a messy folder	File paths with pathlib, automated testing with pytest, the with statement
Build a sales report	Reading CSV files, writing and formatting Excel files
Email a report every Monday	Sending email, keeping passwords safe with .env, scheduling on Mac, Windows and GitHub Actions
Get a daily stock market brief	Calling an LLM from your code with the Gemini API, plus live Google Search

Enroll now and start Day 1 today →

By Day 8, code like this won’t scare you

This is the real script behind the market brief. Today it may look like a wall of text. In 8 days you’ll read it line by line, run it, fix it when it breaks and change it to do your own work.

Why learn to code if AI can write the code?

AI can write the code, but you’re the one building the system, and systems need someone who understands them. It’s like writing: AI can write, but you still need to know how to write to get great results from it.

You don’t have to write every line from memory. You do need to read code and understand what’s going on. That’s what gives you the confidence to use code to solve your own problems.

Copy-pasting code never builds confidence

If you only copy and paste AI code, you’ll always feel one error away from being stuck. Real confidence comes from opening a script and thinking, “I know what this does, and I can change it.” This course builds that feeling, project by project.

Take a peek inside

A day-by-day tour of everything you’ll build.

Your 8-day roadmap

8-day roadmap of the AI Accelerated Python Bootcamp

What you get

25+ hours of step-by-step video across 8 focused days (about 3 hours a day)
6 real projects you keep: split expenses, clean a contact list, organize a messy folder, build an Excel sales report, email it every Monday and get a daily AI market brief
Line-by-line walkthroughs of every AI-written script
Debugging on your own: read tracebacks, fix the 5 most common errors, debug with print and with AI
Automated tests with pytest, so you know your code works before you trust it
Automations that run themselves on your Mac, your Windows PC or in the cloud with GitHub Actions
Call an LLM from your own code with the Gemini API (free key; adding live Google Search is optional and needs a paid key)
The AI Accelerated Learning Method: goal and prompt → AI draft → run → read line by line → improve → test, a workflow you’ll reuse for every project after this course

What students say about learning this way

These reviews are from students of my earlier web development course, taught with the same method.

Reviews from web development students taught with the AI Accelerated Learning Method

Your instructor

I’m Jackson Kailath. I’ve taught 50,000+ students DSA, Python and web development. I hold an MBA from ISB and worked as a Product Manager at Walmart Global Tech. Today I build products with AI every day, and this course teaches the exact way I work.

Why start now

Every month you wait, the gap grows between people who can direct AI and understand its output and people who can’t. With just-in-time learning, you’ll see results within days, not months.

Enroll now and start Day 1 today →

The AI Accelerated Learning mindset: no memorizing, just learn the basics, then learn everything else just in time
Start solving real problems with real-world Python right away, instead of getting stuck on toy exercises
Use AI as your coding partner and learn as you go: AI drafts the code, you understand it, then you improve it
Read and understand AI-written Python line by line, so you always know what your code is doing
Turn a goal into a clear prompt so AI gives you better code from the start
Debug and test your code with confidence, using pytest and AI
Automate real work: files, Excel reports, scheduled emails, and calling an LLM from your own code
Build the understanding you need to move confidently to agentic coding later

Course Content

Day 0 – Start Here
How the course works and the AI Accelerated Learning mindset: learn the basics, then learn the rest just in time. Start here to get the most out of every day.

Welcome

11:00
Course Walkthrough

13:00
How to get the Course Code

Day 1 – Your First AI-Written Script + Coding Setup
🛠 You build: your first AI-written Python script. Write your first prompt, get the code and run it, while setting up VS Code, the terminal, Python, uv and a virtual environment, the same setup you’ll use for every project.

Welcome to Day 1

01:00
Resources for this day
Get your first AI code written – Part 1 (Goal, Prompt )

10:00
Get your first AI code written – Part 2 (Code )

02:48
Prompt
Setting up Code Editor – VS code

10:00
Installing Extensions for Code editor

09:00
A bit more about the Terminal

02:00
Getting our Environment ready – Python, uv, virtual environment

28:00
Terminal Commands for installing – ready reference
Running the AI drafted code

04:00
Terminal Basics

11:00
How we will be installing packages

08:00

Day 2 – Python Foundations (for reading Python)+ Project: Expense Splitter
🛠 You build: Expense Splitter. Learn the core Python you need to read almost any script (types, f-strings, functions, if/else, loops, lists, dictionaries, comprehensions, nested data), then read the AI-written Expense Splitter line by line and change it for a new requirement.

Welcome to Day 2

01:00
Resources for this day
The Plan for this section

03:00
Expense Splitter: Goal and Prompt

13:00
Expense Splitter: Get the AI written code

02:00
Expense Splitter: Running the AI written code

06:00
Foundations : Values and Types

39:00
Foundations: Data Types – 1 (int, float , str , bool)

13:00
Foundations: Data Types – 2 (f-strings)

14:00
Foundations: Functions

16:00
Foundations: Read a Script + Make an edit

31:00
Foundations: Decisions (if else statements)

27:00
Foundations: Conditions ( comparison, and , or , not )

26:00
Foundations: Loops ( for, while, enumerate, loop over files)

34:00
Foundations: List and Dictionary

17:00
Foundations: Indexing, Slicing and Operations

23:00
Foundations: Tuples and Sets

24:00
Foundations: Comprehensions

33:00
Foundations: Nested Lists and Dicts

36:00
Expense Splitter: Read AI written code Line by Line

51:00
Expense Splitter : Modify it to incorporate a requirement

02:00
Prompt

Day 3 – Reading Practice + Project: Contact Deduplicator
🛠 You build: Contact Deduplicator. Practise reading a fresh script line by line, then use AI to make it better.

Welcome to Day 3

01:00
Resources for this day
Plan for this Section, (+ Contact Deduplicator: Goal and Prompt)

14:00
Get the code with AI (Contact Deduplicator)

02:00
Prompt
This is your next Task

01:30
Line by Line discussion on Contact Deduplicator + Q&A

38:00
Q&A discussion Part 2

09:00
Task – Make the Contact Deduplicator better (use AI)

04:00
Solution Discussion

15:00

Day 4 – Debugging and Testing: Fix a Broken Script
🛠 You fix: a broken script. Read a traceback, recognize the 5 most common error types, debug with print and with AI, and use try/except the right way.

Day 5 – Project: Folder Organizer (with pytest)
🛠 You build: Folder Organizer. A script that sorts a messy folder automatically. Learn file paths with pathlib, improve the AI draft into Version 2 and write automated tests with pytest.

Welcome to Day 5

01:00
Resources for this day
Define the Goal – Folder Organizer

20:00
Get the AI draft (Do not run on a real folder – discussed in the video)

13:00
Prompt 1 (to get the code)
Introduction to Path

35:00
Organize Folder Script: Line by Line Discussion Part 1

03:00
Organize Folder Script: Line by Line Discussion Part 2

05:00
Organize Folder Script: Line by Line Discussion Part 3

20:00
Improvements to the First Version (+Prompt to get the improvements done)

09:00
Get the Version 2 Code (with improvements) for Organize Folder Script

01:29
Prompt 2 (to get the code)
Discuss the Version 2 Code of Organize Folder Script in detail

39:00
Pytest (for test cases to automatically test your code) Part 1

02:40
Pytest (for test cases to automatically test your code) Part 2

01:45
Pytest (for test cases to automatically test your code) Part 3

02:13
Pytest (for test cases to automatically test your code) Part 4

12:00
Pytest Example discussion

09:00
Test Cases for Organize Folder Script (using Pytest)

34:00
The with statement pattern (getting ready for the next Section)

20:00

Day 6 – Project: Sales Report Generator (CSV → Excel)
🛠 You build: Sales Report Generator. Turn raw CSV sales data into a polished, formatted Excel report, then refine the code and back it up with tests.

Welcome to Day 6

01:00
Resources for this day
Define the Goal and write the Prompt (Sales Report Generator)

19:00
Get the AI drafted Code

00:21
Prompt (to get the code)
Setting Up and Test-Running the AI Draft: Sample Data, Requirements, and First Excel Report

07:00
Warm up lesson : Reading CSV

16:00
Warm up lesson: Writing Your First Excel File

06:00
Warm up lesson: Formatting Basics

13:00
Line by Line discussion on Sales Report Generator

46:00
Refining the first version of Sales Report Generator

08:00
Changes to version 1 code – Part 1

27:00
Changes to version 1 code – Part 2

15:00
Changes to version 1 code – Part 3

06:00
Run the Modified Report Generator

02:00
Test Cases for Report Generator – Part 1

29:00
Test Cases for Report Generator – Part 2

22:00

Day 7 – Project: Monday Email Reporter (Scheduled Automation)
🛠 You build: Monday Email Reporter. A report that emails itself every Monday. Send HTML emails with attachments, keep passwords safe with .env, and schedule it on Mac, Windows or GitHub Actions.

Welcome to Day 7

01:00
Resources for this day
Define the Goal (and Prompt) – Monday Email Reporter

09:00
Get the AI draft

01:00
Prompt 1 (to get the code)
Env Example file (more on this in upcoming video – “Setting up your .env file “ for more details )

00:06
Place the code in VS code

02:00
Get App Password + Run the code

07:00
How to Store Secrets

06:00
Install pythondotenv – A third party library

01:00
Setting up your .env file

03:39
Warm up Lesson: Send Email

28:31
Warm up Lesson: html and attachment to an Email

18:29
Monday Email Reporter – Line by Line discussion

50:00
Improvements to Version 1 (AI draft)

06:00
Split the Version 1 – AI draft into 2 files

04:00
Prompt 2 ( to split the code into 2 parts)
Edits to Version 1 – Part 1

11:00
Edits to Version 1 – Part 2

42:00
Quick Correction

00:30
Verify our Code

02:00
Mac: Schedule the Monday Report

32:00
Windows: Schedule the Monday Report

19:26
Using Github Actions: Schedule Monday Report – Part 1

12:00
Using Github Actions: Schedule Monday Report – Part 2

06:00
Using Github Actions: Schedule Monday Report – Part 3 (.yml)

11:00

Day 8 – Capstone: AI Stock Market Brief (Gemini API)
🛠 You build: AI Stock Market Brief. Call an LLM from your own code with a free Gemini API key, build an AI-written market brief and add live Google Search results.

Welcome to Day 8

01:00
Resources for this day
Install requirements – google gen ai package

03:00
Get a Free Gemini API Key

03:36
First Programmatic call to Gemini API

20:00
Prompt 1 (first Gemini call)
Market Brief : Define Goal(+prompt)

26:00
Get the Code with AI

00:35
Prompt 2(market report)
Run and Test the AI drafted code

10:34
Line by Line discussion on Market brief – Part 1

54:00
Line by Line discussion on Market brief – Part 2

12:00
API Key for doing google search

01:43
Testing to get the response including google search

03:14

About Course

Build 6 real Python projects in 8 days, even if you’ve never written a line of code.

In the AI age, only fast learning makes sense

This course is for you if…

Start with foundations, then learn just in time

By Day 8, code like this won’t scare you

Why learn to code if AI can write the code?

Copy-pasting code never builds confidence

Take a peek inside

Your 8-day roadmap

What you get

What students say about learning this way

Your instructor

Why start now

What Will You Learn?

Course Content

Day 0 – Start Here How the course works and the AI Accelerated Learning mindset: learn the basics, then learn the rest just in time. Start here to get the most out of every day.

Welcome

Course Walkthrough

How to get the Course Code

Day 1 – Your First AI-Written Script + Coding Setup 🛠 You build: your first AI-written Python script. Write your first prompt, get the code and run it, while setting up VS Code, the terminal, Python, uv and a virtual environment, the same setup you’ll use for every project.

Welcome to Day 1

Resources for this day

Get your first AI code written – Part 1 (Goal, Prompt )

Get your first AI code written – Part 2 (Code )

Prompt

Setting up Code Editor – VS code

Installing Extensions for Code editor

A bit more about the Terminal

Getting our Environment ready – Python, uv, virtual environment

Terminal Commands for installing – ready reference

Running the AI drafted code

Terminal Basics

How we will be installing packages

Welcome to Day 2

Resources for this day

The Plan for this section

Expense Splitter: Goal and Prompt

Expense Splitter: Get the AI written code

Expense Splitter: Running the AI written code

Foundations : Values and Types

Foundations: Data Types – 1 (int, float , str , bool)

Foundations: Data Types – 2 (f-strings)

Foundations: Functions

Foundations: Read a Script + Make an edit

Foundations: Decisions (if else statements)

Foundations: Conditions ( comparison, and , or , not )

Foundations: Loops ( for, while, enumerate, loop over files)

Foundations: List and Dictionary

Foundations: Indexing, Slicing and Operations

Foundations: Tuples and Sets

Foundations: Comprehensions

Foundations: Nested Lists and Dicts

Expense Splitter: Read AI written code Line by Line

Expense Splitter : Modify it to incorporate a requirement

Prompt

Day 3 – Reading Practice + Project: Contact Deduplicator 🛠 You build: Contact Deduplicator. Practise reading a fresh script line by line, then use AI to make it better.

Welcome to Day 3

Resources for this day

Plan for this Section, (+ Contact Deduplicator: Goal and Prompt)

Get the code with AI (Contact Deduplicator)

Prompt

This is your next Task

Line by Line discussion on Contact Deduplicator + Q&A

Q&A discussion Part 2

Task – Make the Contact Deduplicator better (use AI)

Solution Discussion

Day 4 – Debugging and Testing: Fix a Broken Script 🛠 You fix: a broken script. Read a traceback, recognize the 5 most common error types, debug with print and with AI, and use try/except the right way.

Welcome to Day 4

Resources for this day

Reading a traceback

The big 5 Error Types

using Print for debugging

using AI for debugging

The try except pattern

Do not use try except to hide an error

Challenge – fix a script

Day 5 – Project: Folder Organizer (with pytest) 🛠 You build: Folder Organizer. A script that sorts a messy folder automatically. Learn file paths with pathlib, improve the AI draft into Version 2 and write automated tests with pytest.

Welcome to Day 5

Resources for this day

Day 0 – Start Here
How the course works and the AI Accelerated Learning mindset: learn the basics, then learn the rest just in time. Start here to get the most out of every day.

Day 1 – Your First AI-Written Script + Coding Setup
🛠 You build: your first AI-written Python script. Write your first prompt, get the code and run it, while setting up VS Code, the terminal, Python, uv and a virtual environment, the same setup you’ll use for every project.

Day 3 – Reading Practice + Project: Contact Deduplicator
🛠 You build: Contact Deduplicator. Practise reading a fresh script line by line, then use AI to make it better.

Day 4 – Debugging and Testing: Fix a Broken Script
🛠 You fix: a broken script. Read a traceback, recognize the 5 most common error types, debug with print and with AI, and use try/except the right way.

Day 5 – Project: Folder Organizer (with pytest)
🛠 You build: Folder Organizer. A script that sorts a messy folder automatically. Learn file paths with pathlib, improve the AI draft into Version 2 and write automated tests with pytest.

Day 6 – Project: Sales Report Generator (CSV → Excel)
🛠 You build: Sales Report Generator. Turn raw CSV sales data into a polished, formatted Excel report, then refine the code and back it up with tests.

Day 7 – Project: Monday Email Reporter (Scheduled Automation)
🛠 You build: Monday Email Reporter. A report that emails itself every Monday. Send HTML emails with attachments, keep passwords safe with .env, and schedule it on Mac, Windows or GitHub Actions.

Day 8 – Capstone: AI Stock Market Brief (Gemini API)
🛠 You build: AI Stock Market Brief. Call an LLM from your own code with a free Gemini API key, build an AI-written market brief and add live Google Search results.