
4.0
Course Rating
3.2k+
Learners
Not set
Total Content
Beginner
Level
๐ 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.
โน0
โน399
Discount 100% off
Course Fee
โน0
Worth of
โน399
Your Savings
100% Off
Benefits
Get Full Course Access
Earn a Verified Certificate
Pay as Much as You Wish
Risk-free. Start learning today!
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 โก
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
LiveLearn live with instructors, ask questions, and get real-time guidance. Previous recordings are included.
Topic Explanation
Learn concepts live with practical examples and guidance.
Doubt Clearing Sessions
Ask questions, clear doubts, and get help when you need it.
Hands-on Projects
Work on projects with guidance and support from mentors.
Mock Interview
Practise interviews, exchange feedback, and build confidence.
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
Senior Frontend Engineer, StudioLabs
Aarav has mentored 1200+ learners and specializes in production UI systems and scalable frontend architecture.
LinkedIn
Ananya Mehta
Design Technologist, CraftLabs
Ananya blends design and code to help learners ship portfolio-ready projects.
LinkedIn
Kabir Sayed
Frontend Mentor, PixelWorks
Kabir focuses on clean code, accessibility, and practical frontend delivery.
LinkedInThis 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
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
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
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
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
Cloud Computing Learner
Join Our Community, Ask Questions
Frequently Asked Questions
You will learn backend development using Python, build APIs, containerize applications with Docker and deploy scalable services on AWS.
Basic Python programming knowledge is recommended, but the course gradually introduces backend development concepts.
Yes, all sessions are recorded so you can revisit lessons and practice deployment steps anytime.
Yes, students build real backend projects including APIs, Docker containers and AWS deployment pipelines.
You receive guidance on improving backend architecture, debugging deployment issues and optimizing cloud infrastructure.
Learners
3,204+
Duration
Not set
Get Life Time Access
โน0
โน399
100% off
Get Life Time Access
โน0
โน399
100% off



