Course Content
00: Resources
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Links to All codes
01: Introduction to the course
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AI ka chilla started now
02:15
AI KA Chilla-2026 | Learn AI in 40 Days in 2026 #NewYear #newyear2026
06:43
Day-1: Introduction to the course and plans
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Start of the course and Happy New Year
04:17
Enroll in AI ka chilla LMS check your email
05:14
Discord community link for AI ka chilla
09:31
Meeting details for live classes and question answer sessions
06:16
Know your instructor
12:25
Plan of the course AI ka chilla learning map
17:25
Daily tasks for students Important
00:38
Questions No. 1: Non structured and structured data analysis
02:41
Question No. 2: Projects for different sectors for using AI
02:04
Question no. 3: How to pitch ourselves on linkedIn after the course?
03:00
Day-2: Python and other Software Installations + Integration
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Introduction to Python as programming language
15:52
Guido von Rossum creator of Python as programming language
01:28
Five software installation for the course
16:40
Create new user account for fresh installations and admin privileges
15:21
Install python with a fresh start from Zero
10:16
Install VScode with fresh start
02:56
VScode options while installations goo for future coding
05:40
Install git and gitBash in windows
08:01
Install miniconda for AI and python environments
13:48
gitBash – miniconda – vscode integration | step by step guide
23:04
miniconda and gitbash integration trouble shooting – Important
14:40
Day-3: Essentials (GitHub, GitHub student/teacher developer pack, Python and learning)
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GitHub account and GitHub student developer pack
18:32
GitHub account in VScode for synchronization
06:04
Tools to plan your tasks for longer run and learning methodology
22:56
Your first line of code | use python with three ways
33:43
Learn python crash course before we proceed
01:25
Three (3) way learning strategy | Tips to Master coding and learning by doing
08:39
We have covered so far…..
02:00
Trouble shooting and errors you might be having
09:03
Important login IDs and signups for AI journey
24:15
News and Newsletters for AI updates on regular basis
08:29
Mobile price vs. Your Laptop price Data analysis
04:58
Practice to use discord server private channel for the course
07:45
Question No. 1: What is the plan for learning ahead
03:08
Question No. 2: How can we post on LinkedIN from News?
02:51
Question No. 3: Data analysis plan from now on
02:20
Question No. 4: Industry vs. Academia for AI
02:45
Question No. 5: Integration of AI in industrial Tools
02:39
Day-4: Python Programming A-Z
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Learn python crash course before we proceed (This was also in the pre-requisite)
11:55:09
Jupyter notebooks (Introduction) | comments and use in python
26:38
Install Jupyter lab and Jupyter notebooks windows
16:22
Jupyter notebooks use in google colab and kaggle
01:59
Jupyter notebook in VScode
08:45
Why VScode is my favourite IDE (Integrated Development Environment)
36:08
Environments and conflicts | conda, mamba, venv (virtual) environments for installing softwares
57:12
GitHub copilot and Snake game development under 5 minutes
08:06
Networking is important for AI learning
14:19
Portfolio is important for AI Engineering journey these days
09:20
Free vs. Paid tools for portfolio buildup
01:29
Tools to build portfolio for AI engineering Journey
18:22
Question No. 1 from Students
01:45
Question No. 2 from Students
02:33
Question No. 3 from Students
01:38
Question No. 4 from Students
03:17
Question No. 5 from Students
02:29
Question No. 6 from Students
00:32
MarkDown in 72 minutes crash course
01:11:24
Day-5: Networking and Portfolio for AI or Data Science Students
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Networking using LinkedIN | Reading Material
Portfolio making | Understanding and building portfolio for Data Science and AI Students and Developers
02:37:53
Day-6: Git and GitHub | A-Z Guide using only command line | Beginner to Expert
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Intro to Git
07:55
How git works?
01:55
Is git free?
01:52
Git learning pathway in Two Steps
01:34
Install git
01:56
Git Bash installation (ignore if you already installed)
08:01
Verify your installation (Important)
01:33
Configure your local Git with username and email from gitHub
05:32
Create a local repository or folder
06:54
Initialize git to turn on track changes
02:40
git commands | git add and commit to stage and store changes
11:32
git log or history of commits
02:41
Restore a file to a specific commit
01:02
Push local repository to github account | Important
09:27
Day-7: Git, GitHub and VScode use as professionals
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VScode to initialize git repository using GUI
06:34
Local to online git repository on VScode and GitHub
07:06
Limit for file sizes on GitHub
01:41
Connect your current repo to GitHub with VScode
03:03
Work with online repositories of GitHub
12:03
Add collaborators in GitHub repositories | Work in a team
01:48
Day-8: Large Language Models (LLMs)
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01-What are Large Language Models and how do they work?
16:32
02-Trending List of LLMs and their use cases
11:32
03-Differences in LLMs vs. Fine Tuned LLMs vs. RAG based LLMs
18:38
04-Understanding RAG based Bots (Retrieval Augmented Generation)
12:12
05-Augmented Generation to improve LLM RAG and CAG
25:26
06-Earn USDs using RAG and CAG
23:36
07-Ten Lessons from an expert: Enterprise level RAG based apps
19:14
Day-9: Generative AI (GenAI) and Agentic AI
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01-What is Generative AI? Easy way to learn
16:47
02-GenAI applications for project development
04:01
03-GenAI for online earning by making projects and providing services
26:02
04-GenAI APIs to make tools and applications for earning
15:49
05-GenAI vs AgenticAI what is the difference?
13:58
06-Hundred Plus GenAI projects to earn online
06:03
Day-10: VScode + GitHub copilot and VIBE coding | Data and Data Components
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VScode IDE and Alternatives to GitHub Copilot for VScode
11:22
VIBE coding with IDEs and coding agents for fast programming
10:59
Product requirements document | PRD is important
13:33
Workflow for Product development and Finding a Niche
21:44
Data and Types of Data | Scales or levels of measurement
28:53
Question:1-RAG based Apps and future career
01:41
Define data in an easy way
01:40
Categorical vs. Numerical data | Qualitative vs. Quantitative Data
02:45
Text Data of Natural Language | NLP | Natural Language Processing
04:27
Data in spreadsheets and Important components of data
37:38
Day-11: Data, Data Gathering and Project based Product Development with Trending Topic
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Variables and Metadata about variables
09:34
Which data should we work on and why?
29:25
First hand information gathering about AI and Data Science
09:04
Google sheet for Data Gathering websites
03:46
Save this sheet in your pc for future
00:37
Valid and Authentic Resources to get data
27:08
Task for students | Use Pandas Profiling for example dataset
00:50
Important Notes for the Data Measurements and Scales
Day-12: Data and Pandas profiling | Exploratory Data Analysis (EDA)
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Task for Today
01:27
Plan to use pandas- or ydata- profiling for Automatic EDA
07:39
EDA project with pandas- or ydata- profiling for three different datasets
23:03
Automatic EDA in few seconds using data from kaggle.com
09:22
Day-13: Data Gathering and automatic EDA with Top Libraries
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Data Gathering Using Python APIs | wbdata, FAOSTAT, Eurostat, yfinance for Analysts & Scientists
01:15:30
Complete EDA with dTale library in Python in seconds with only 5 lines of code
14:46
Pandas- or ydata-profiling for time series analysis and automatic EDA
06:53
dtale library for automatic EDA for any data
13:04
Data Collection is important for EDA
Descriptive Statistics is important to learn for EDA
Inferential Statistics and Hypothesis Testing for comparison
Day-14: Do EDA in few seconds with these Python Libraries
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PyGwalker for Automatic Data Visualization and EDA
15:17
Sweetviz use in python comes with errors
14:29
Sweetviz is working fine here for automatic EDA
03:37
SKIMPY python library for data understanding
11:08
Dataprep python library for EDA of Data
09:23
LIDA python library for EDA and auto data analysis
21:05
Lida Huggingface take s alot of space
05:00
All codes for these libraries are here
Must Read this guide about EDA
EDA with LIDA and A book chapter about EDA to understand outputs of Lida
03:45
LIDA is working using API keys | I just Bought
11:12
Always close the server when you are running server based apps
00:45
Day-15: AI for Vibe Coding
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Pandas AI library for AI data analysis
00:00
Basic Data Knowledge is important before you use AI for Data Analysis
06:00
AI based IDE Cursor for APP development in Seconds
26:59
Antigravity is a great alternative to VScode to develop application using agentic AI in seconds
32:08
Day-16: Antigravity and Project with Agentic AI for Kaggle Data Grandmaster Ranking
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Google Antigravity is RAM Hungry
03:28
Google Antigravity IDE can work as a developer in 21000 PKR only for an year
07:15
Google One AI Enhanced plans for Antigravity
06:08
Kaggle Dataset Grandmaster guide A to Z in urdu using Google Antigravity AI Agents
55:59
Important Task Assignment for Students
00:45
AI Ka Chilla 2026
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