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๐Ÿ“Š Python for AI and Machine Learning from Scratch course preview

4.0

Course Rating

3.2k+

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Total Content

Beginner

Level

Level: Beginner

๐Ÿ“Š Python for AI and Machine Learning from Scratch

Master Python for AI and machine learning by learning programming fundamentals, loading, cleaning, analyzing, and visualizing real datasets with NumPy, Pandas, and Matplotlib.

Lifetime Access

Learn anytime. No deadlines.

Session Recordings

Rewatch sessions and learn at your pace.

Mentor Support

Get guidance and clear your doubts.

Community Access

Learn, connect, and grow together.

Tools & Technologies You'll Use

VS Code

Python

ChatGPT

Numpy

Lifetime Access

Learn at your own pace, anytime, anywhere.

Certificate

Earn a verified certificate upon completion.

Hands-on Projects

Build real-world projects for your portfolio.

Mentor Support

Get guidance and clear your doubts.

Live Sessions Including

Topic Explanation

Learn concepts live with practical examples.

Doubt Clearing Sessions

Ask questions, clear doubts, and get help.

Hands-on Projects

Work on projects with guidance and support.

Mock Interview

Practise interviews and exchange feedback.

Session dates and times are scheduled based on community demand.

Learn First. Pay Later.

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Benefits

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Earn a Verified Certificate

Pay as Much as You Wish

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After this course, you can

Load and clean real datasets

Visualize data with Python

Prepare data for ML models

Build data analysis pipelines

Course Curriculum

Follow this structured learning path to build skills from beginner to advanced.

Lessons

Start here after enrolling. These lessons build your core foundation step by step.

Why Python Won the AI Race While Other Languages Watched

14 min

Installing Python and Setting Up VS Code Without Tears

17 min

Jupyter Notebooks: The Place Every ML Person Actually Lives

12 min

Virtual Environments: Stopping Your Projects From Fighting Each Other

13 min

Pip and conda: Installing Things, and Knowing Which One to Use

14 min

Git Basics: Saving Your Work Before You Break It

17 min

Variables and Data Types: Boxes, Labels, and What Goes Inside

16 min

Numbers, Operators, and the Maths Python Does for You

18 min

Strings and String Methods: Text Is Data Too

13 min

If, elif, else: Teaching Your Code to Make Decisions

14 min

Loops: Doing Boring Things 10,000 Times Without Complaining

15 min

Functions: Write It Once, Use It Forever

12 min

Lists: The Workhorse You Will Use Every Single Day

17 min

Tuples: Lists That Refuse to Change, and Why That Helps

15 min

Dictionaries: Looking Things Up by Name, Not by Number

13 min

Sets: The Fastest Way to Kill Duplicates โšก

19 min

Nesting: Lists of Dicts, Dicts of Lists, and Real-World Shapes

17 min

Picking the Right Structure So Future-You Says Thank You

19 min

List Comprehensions: Three Lines Become One

15 min

Lambda, map, and filter: Tiny Functions With No Name

15 min

Reading a Traceback Instead of Panicking at Red Text

14 min

Try, except, finally: Handling Errors on Purpose

15 min

Raising Your Own Errors, and Useful Error Messages

16 min

Modules and Imports: Splitting Code Into Files

15 min

Reading and Writing Files, and the `with` Statement

19 min

CSV Files: The Format the Whole Data World Runs On

18 min

JSON: How APIs and Python Talk to Each Other

15 min

Excel Files, Because Your Client Will Send One

18 min

Messy Data, Encodings, and the File That Broke Your Script

15 min

Mini Project: Turn a Raw Data Dump Into Clean Records

17 min

Why Lists Are Too Slow, and Arrays Are Not

15 min

Creating Arrays, Shapes, and dtypes

19 min

Indexing and Slicing: Grabbing Exactly What You Need

14 min

Vectorised Maths: Doing Away With the Loop

17 min

Broadcasting: The Rule That Confuses Everyone Once

13 min

Matrices, Axes, and the Shape Errors You Will Definitely Hit

16 min

Series and DataFrames: Spreadsheets That Obey Code

15 min

Loading CSV and Excel Into a DataFrame

15 min

First Look: head, info, describe, and What They Tell You

16 min

Selecting, Filtering, and Sorting Rows

14 min

Plots With Matplotlib, and the Capstone: Raw File to Real Insight

18 min

Live Session Recordings

Live

Learn live with instructors, ask questions, and get real-time guidance. Previous recordings are included.

Topic Explanation

Learn concepts live with practical examples and guidance.

Weekly Once

Doubt Clearing Sessions

Ask questions, clear doubts, and get help when you need it.

Weekly Twice

Hands-on Projects

Work on projects with guidance and support from mentors.

Monthly Once

Mock Interview

Practise interviews, exchange feedback, and build confidence.

Daily

Bonus Resources

Get bonus content and resources to practise, revise, and go deeper.

Study Materials

Cheat Sheets

Interview Q&A

PYQ PDFs

PPTs

Quizzes

Requirements

What you should have before starting the course.

Basic Python programming knowledge

No AI or ML experience required

A computer with Python installed

Willingness to work with real datasets

Curriculum Designed & Verified by Industry Experts

Learn skills and concepts validated by industry professionals who use them in real-world work every day.

Aarav Sharma

Aarav Sharma

Senior Frontend Engineer, StudioLabs

Aarav has mentored 1200+ learners and specializes in production UI systems and scalable frontend architecture.

LinkedIn
Ananya Mehta

Ananya Mehta

Design Technologist, CraftLabs

Ananya blends design and code to help learners ship portfolio-ready projects.

LinkedIn
Kabir Sayed

Kabir Sayed

Frontend Mentor, PixelWorks

Kabir focuses on clean code, accessibility, and practical frontend delivery.

LinkedIn

This course is for you if you want to

Wherever you are in your journey, this course helps you learn, build, and grow with confidence.

Students & Fresh Graduates

Build a strong foundation and turn what you learn into practical experience.

Learn from beginner to advanced

Build real-world projects

Get feedback and improve

Working Professionals

Upgrade your skills and apply new knowledge directly in your career.

Learn in-demand skills

Apply directly to your work

Grow with practical knowledge

Career Switchers

Follow a clear path as you transition confidently into a new career.

Structured learning path

Hands-on practice

Mentor support at every step

Freelancers & Creators

Sharpen your craft and deliver better results for your clients and audience.

Work on client-ready projects

Improve efficiency and quality

Stay current with modern tools

For anyone who wants to learn, build, and grow. All you need is curiosity and a willingness to take the first step.

What you will get after completing this course

Illustration of a verified course completion certificate

Receive an official course completion certificate

Live verification URL with PDF and downloadable option

Signed by your course designer and the Director of Shattak

Carries your name, course title, and completion date

Recruiters can check it in seconds from your LinkedIn or resume

Pay After Certification

Pay whatever you feel it is worth, only after you get certified. No questions asked.

Hear From Learners Who've Taken This Course

Honest feedback from learners who completed the live sessions.

4.9

52

This course gave me a clear understanding of backend development and cloud deployment. Learning Python APIs along with Docker and AWS made the workflow feel very practical. I finally understood how real production systems are built and deployed.

Rahul Verma

Rahul Verma

Backend Developer Intern

4.8

39

The combination of Python backend development and Docker containerization was explained really well. I was able to deploy my first cloud based API on AWS after finishing the project modules. Very practical and industry focused course.

Arjun Patel

Arjun Patel

Software Engineering Student

4.7

41

I had basic Python knowledge but this course helped me understand scalable backend architecture. The lessons on containerization, deployment pipelines and AWS services were very useful for real world development.

Rohit Mehta

Rohit Mehta

Junior Backend Developer

5

57

A very well structured course for learning modern backend engineering. The step by step explanation of APIs, Docker containers and AWS deployment helped me understand how scalable systems actually work in production.

Sneha Kapoor

Sneha Kapoor

Cloud Computing Learner

See what they have built

KS

Karan Sharma

Python REST API Backend Service

Python REST API Backend Service

268 Likes

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AB

Aditya Banerjee

Dockerized Microservice Deployment

Dockerized Microservice Deployment

318 Likes

View Live
NS

Neha Singh

AWS Cloud Backend Infrastructure Setup

AWS Cloud Backend Infrastructure Setup

191 Likes

View Live
RG

Ritika Ghosh

Scalable Backend Application Deployment

Scalable Backend Application Deployment

356 Likes

View Live

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Get Life Time Access

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