Deep Learning & Neural Networks

Build CNNs, RNNs and transformers from scratch with TensorFlow

★ 4.7 (8,320 students) · 48 hours total · Certificate of completion

Created by Rahul Mehta

What you'll learn

Design and train deep neural networks from scratch

Build CNNs for image classification and object detection

Implement RNNs and LSTMs for time series and NLP

Fine-tune pre-trained transformer models (BERT, GPT)

Track experiments with Weights & Biases

Deploy deep learning models to production APIs

About This Course

Dive deep into neural network architectures. Build convolutional networks for image recognition, recurrent networks for sequences, and transformers for language. Each module ends with a project you ship and explain to your cohort.

Course Curriculum

10 weeks · 48 hours total

Requirements

Completed ML with Python or equivalent
Linear algebra fundamentals
Python proficiency

Your Instructor

Rahul Mehta

AI & Machine Learning Expert

An industry practitioner actively working in AI & Machine Learning. Brings real-world experience and production-grade examples to every session. Known for clear explanations and strong student outcomes.

★ 4.7 instructor rating · 8,320 students taught

Student Reviews

4.7

★★★★★

Course Rating

5★ 68%

4★ 24%

3★ 6%

2★ 1%

1★ 1%

Ravi M.

2 weeks ago

★★★★★

Absolutely fantastic course! The instructor explains complex concepts with ease, and the hands-on projects really solidified my understanding. Already applied several techniques at work.

Sakshi T.

1 month ago

★★★★★

Best course I've taken on this topic. The live sessions are incredibly valuable — you can ask questions in real time and get immediate feedback. Worth every rupee!

Karthik R.

1 month ago

★★★★

Very practical and well-paced. The project-based approach sets this apart from other online courses. Would appreciate a few more practice exercises, but overall excellent.

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