
Level: Beginner
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.
4.0
3.2k+ learners
Duration
0 min
Learners
3.2k+ Enrolled Students
Session Recording
Lifetime Access
Post Session
Mentor support
Session Schedule
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ā¹399
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Course Fee
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Includes
⢠Expert Designed Curriculum
⢠Doubt Clearing Session
⢠Forever Community Access
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
Expand or explore the full learning path.
Lessons
Start here after enrolling. These lessons form the core learning path for the course.
Why Python Won the AI Race While Other Languages Watched
Installing Python and Setting Up VS Code Without Tears
Jupyter Notebooks: The Place Every ML Person Actually Lives
Virtual Environments: Stopping Your Projects From Fighting Each Other
Pip and conda: Installing Things, and Knowing Which One to Use
Git Basics: Saving Your Work Before You Break It
Variables and Data Types: Boxes, Labels, and What Goes Inside
Numbers, Operators, and the Maths Python Does for You
Strings and String Methods: Text Is Data Too
If, elif, else: Teaching Your Code to Make Decisions
Loops: Doing Boring Things 10,000 Times Without Complaining
Functions: Write It Once, Use It Forever
Lists: The Workhorse You Will Use Every Single Day
Tuples: Lists That Refuse to Change, and Why That Helps
Dictionaries: Looking Things Up by Name, Not by Number
Sets: The Fastest Way to Kill Duplicates ā”
Nesting: Lists of Dicts, Dicts of Lists, and Real-World Shapes
Picking the Right Structure So Future-You Says Thank You
List Comprehensions: Three Lines Become One
Lambda, map, and filter: Tiny Functions With No Name
Reading a Traceback Instead of Panicking at Red Text
Try, except, finally: Handling Errors on Purpose
Raising Your Own Errors, and Useful Error Messages
Modules and Imports: Splitting Code Into Files
Reading and Writing Files, and the `with` Statement
CSV Files: The Format the Whole Data World Runs On
JSON: How APIs and Python Talk to Each Other
Excel Files, Because Your Client Will Send One
Messy Data, Encodings, and the File That Broke Your Script
Mini Project: Turn a Raw Data Dump Into Clean Records
Why Lists Are Too Slow, and Arrays Are Not
Creating Arrays, Shapes, and dtypes
Indexing and Slicing: Grabbing Exactly What You Need
Vectorised Maths: Doing Away With the Loop
Broadcasting: The Rule That Confuses Everyone Once
Matrices, Axes, and the Shape Errors You Will Definitely Hit
Series and DataFrames: Spreadsheets That Obey Code
Loading CSV and Excel Into a DataFrame
First Look: head, info, describe, and What They Tell You
Selecting, Filtering, and Sorting Rows
Plots With Matplotlib, and the Capstone: Raw File to Real Insight
Live Session Content
This topic will be taught live in an interactive session, allowing you to engage with the instructor and ask questions in real time. While recordings will be available, attending live offers the best learning experience.
Post Session Study Material
This section will be unlocked after the session. You'll get access to exclusive bonus content, additional examples, and on-demand resources to support continuous learning and deeper understanding.
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
Tools you are going to use
VS Code

Python
ChatGPT
Numpy
Learn From Expert Instructor
Meet the mentors leading the live sessions.

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.
LinkedInYou should join this course if you
Students & Fresh Graduates
Build a strong portfolio
Learn from live mentors
Get feedback on your work
Working Professionals
Upgrade frontend skills
Ship real projects
Join a peer community
Career Switchers
Structured learning path
Hands-on practice
Guided sessions
Freelancers & Creators
Build client-ready sites
Improve delivery speed
Learn modern workflows
What you will get after completing this course
Receive an official course completion certificate
Earn skill-focused feedback from mentors
Showcase your project in the Shattak community
Access lifetime notes and references
Stay connected with instructors for guidance
Completion bonus
Certificate access, community showcase, and lifetime mentor guidance.
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.
Shattak courses are primarily self-paced and may include lessons, recordings, assignments, projects, and additional learning resources. Live sessions may also be conducted based on community demand.
Yes. If a live session is conducted for your course, you can access the recording and revisit the content at your own pace.
Yes. Shattak has a learning community where you can ask questions, interact with other learners, share your progress, and get guidance from mentors and peers.
Not always. Each course clearly mentions its requirements and the level of experience needed. Many courses are designed for complete beginners.
Yes. You can earn a course completion certificate after completing the required learning materials and submitting the required assignments or projects.
Yes. You can add your certificate to your LinkedIn profile, resume, portfolio, and other places where you want to showcase your learning and achievements. You may also use it for academic or professional purposes where applicable.
All Shattak courses are free to enroll in and start learning. After completing the course and earning your certificate, you can choose how much to pay from ā¹0 to ā¹10,000. Pay what you feel the learning experience was worth, with no questions asked.
You can explore courses by browsing different topics, skills, categories, or career paths. Each course page provides information about what you will learn, requirements, curriculum, and completion benefits.
Yes. Before enrolling, you can explore the course overview, curriculum, learning outcomes, requirements, and other details to understand what the course offers.
Simply open the course page and click Enroll. All courses are free to enroll in, so you can start your learning journey without paying upfront.
After enrolling, you will be redirected to your course workspace. From there, you can access your lessons and follow the learning path step by step.
Most courses allow you to learn at your own pace. However, some assignments, live sessions, or certification requirements may have specific deadlines.
Depending on the course, you may get access to: ⢠Self-paced lessons ⢠Live sessions based on community demand ⢠Session recordings ⢠Assignments and hands-on projects ⢠Bonus learning resources ⢠Mentor and peer community support ⢠Doubt-clearing and guidance ⢠Course completion certificates
You can ask questions through the learning community and connect with other learners. Depending on the course, you can also receive guidance from mentors and peers.
After completing the required lessons, assignments, and other course requirements, you can submit your work for certification. Once certified, you can access and share your certificate.
If you are an industry professional or expert and want to teach on Shattak, you can apply to become a mentor and create a course or learning experience based on your expertise.
Starting From
TBD
Duration
0 min
Get Life Time Access
ā¹0
ā¹399
100% off
Get Life Time Access
ā¹0
ā¹399
100% off



