Shattak

Roadmap

šŸ¤– Deep Learning with Neural Networks and TensorFlow hero

Level: Beginner

šŸ¤– Deep Learning with Neural Networks and TensorFlow

Build a strong foundation in deep learning by creating neural networks from scratch. Learn perceptrons, activation functions, backpropagation, and train real models with Python.

5.0

2.3k+ learners

Duration

0 min

Learners

2.3k+ Enrolled Students

Session Recording

Lifetime Access

Post Session

Mentor support

Session Schedule

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₹499

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Worth of

₹499

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Includes

• Expert Designed Curriculum

• Doubt Clearing Session

• Forever Community Access

After this course, you can

Build neural networks from scratch

Train deep learning models

Improve model performance

Solve real AI problems

Course Curriculum

Expand or explore the full learning path.

Lessons

Start here after enrolling. These lessons form the core learning path for the course.

What Deep Learning Really Is (And When It Beats Classic Machine Learning)

Activation Functions: How Networks Learn to Bend

Forward and Backpropagation: Guess First, Then Learn From the Mistake

Loss Functions and Optimizers: Measuring "How Wrong" and Getting Less Wrong

Loss Functions and Optimizers: Measuring "How Wrong" and Getting Less Wrong

Regularization: So Models Learn Instead of Memorize

Regularization: So Models Learn Instead of Memorize

Your First Model With the Keras Sequential API

Compiling a Model: Loss, Optimizer, Metrics

Training, Validation, and Reading the Learning Curves

The Functional API: For Models That Branch and Merge

Saving, Loading, and Using Callbacks

Why PyTorch Feels Different From Keras

Tensors, Autograd, and the Computation Graph

Building a Model With nn.Module

Writing Your Own Training Loop (And Understanding Every Line)

Datasets, DataLoaders, and Batching

Saving Models and Moving Work Onto the GPU

The Big Idea: Don't Start From Scratch

Pretrained Models and Where to Find Them

Feature Extraction vs Fine-Tuning

Transfer Learning in Keras, Step by Step

Transfer Learning in PyTorch, Step by Step

Common Mistakes and How to Dodge Them

Computer Vision: Teaching Machines to See

NLP: Teaching Machines to Read

Time Series: Teaching Machines to Predict What Comes Next

When Deep Learning Is the Right Tool for the Job

When Deep Learning Is Overkill, and What to Use Instead

Where to Go Next: Your Roadmap After This Course

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

Familiarity with machine learning basics

Understanding of linear algebra

A computer with Python installed

Tools you are going to use

OpenCV

OpenCV

TensorFlow

TensorFlow

PyTorch

PyTorch

Keras

Keras

Python

Python

NumPy

NumPy

Learn From Expert Instructor

Meet the mentors leading the live sessions.

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

You 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

Completion certificate

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.

4.8

24

Clear structure, solid examples, and a fast pace that keeps you engaged.

Riya Jain

Riya Jain

B.Tech, NIT Trichy

4.6

18

Practical sessions with feedback that helped improve my portfolio.

Kabir Singh

Kabir Singh

Frontend Intern, PixelWorks

4.9

12

Loved the structure and the live walkthroughs.

M

Meera Patel

Design Graduate

See what they have build

ZS

Zainab Shaikh

Portfolio Landing Page

Portfolio Landing Page

300 Likes

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DS

Devendra Singh

Product Marketing Site

Product Marketing Site

214 Likes

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NA

Nadia Ahmed

Interactive Web Story

Interactive Web Story

183 Likes

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Get Life Time Access

₹0

₹499

100% off

Get Life Time Access

₹0

₹499

100% off