Deep Learning with TensorFlow & PyTorch: Build Neural Networks from Scratch

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Deep Learning with TensorFlow & PyTorch

Master deep learning concepts and practical implementation using TensorFlow and PyTorch. Learn about neural networks, CNNs, RNNs, and real-world.

Course Overview

This course provides a deep dive into the fundamentals of deep learning using TensorFlow and PyTorch. You will learn about neural networks, backpropagation, convolutional and recurrent neural networks, and various deep learning architectures. Hands-on coding exercises and real-world projects will help you build AI models effectively.

FAQ

No prior experience is required. The course teaches both from the ground up.

Both are widely used. The course helps you understand strengths of each through practical examples.

Yes, and you'll learn how to train models efficiently using cloud platforms like Google Colab.

Yes, it prepares you for roles like deep learning engineer, AI developer, or ML researcher.

Course curriculum

Deep Learning-Quiz
0:10:0

Requirment

Solid Python programming skills
Basic understanding of machine learning concepts
Familiarity with linear algebra and calculus (helpful but not mandatory)
A laptop with Python, TensorFlow, and PyTorch installed (or use Google Colab)

Outcomes

Understand core deep learning concepts (e.g., CNNs, RNNs, transfer learning)
Build and train models using both TensorFlow and PyTorch
Apply deep learning to real tasks like image and text classification
Learn to debug, tune, and optimize neural networks
Complete portfolio-ready deep learning projects

₹3999

~~₹4999~~

language
English
Duration
00h 10m
Level
beginner
Expiry period
Lifetime
Certificate
Yes