TRACK 21•Deep Learning Track•ADVANCED

Deep Learning

Name: Deep Learning
Price: 3499.00 INR
Availability: InStock

Deep learning with PyTorch — MLP, CNN, RNN, LSTM, attention, and transfer learning.

Transformer ArchitecturesPyTorch & GPU ImplementationsFull Syllabus Access

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Instructor

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13 Modules

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13 Lessons & Labs

Enrollment1-Year Full Access

₹3,499

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Instant 24/7 course activation & access

1-Year full access to all 13 modules & labs

Verified Certificate of Completion

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Overview & Outcomes

Course Learning Objectives

Deep learning with PyTorch. MLP, CNN, RNN, LSTM, GRU, embeddings, attention, and transfer learning. Learn to train, evaluate, and debug production deep learning models.

Core Curriculum Competencies

What you'll master

Deep neural network training dynamics & vanishing/exploding gradients
Weight initialization: Xavier/Glorot, He/Kaiming & Orthogonal
Modern optimizers: Adam, AdamW, RMSprop & learning rate schedulers

Regularization: Dropout, Batch Normalization & Layer Normalization

PyTorch fundamental tensors, custom autograd Functions & nn.Module

GPU acceleration, mixed precision (FP16/BF16) & training loops

Syllabus & Modules

Course Curriculum

A comprehensive breakdown of all modules, theory readings, interactive quizzes, and compiler practice labs.

Module 1: Introduction to PyTorch

1 Lessons

1.1Introduction to PyTorchREADING

Module 2: Tensors, Autograd & Computation Graphs

1 Lessons

2.1Tensors, Autograd & Computation GraphsREADING

Module 3: Multi-Layer Perceptrons (MLP)

Locked

3.1Multi-Layer Perceptrons (MLP)READING

Module 4: Convolutional Neural Networks (CNN)

Locked

4.1Convolutional Neural Networks (CNN)READING

Module 5: Recurrent Neural Networks (RNN)

Locked

5.1Recurrent Neural Networks (RNN)READING

Module 6: Long Short-Term Memory (LSTM)

Locked

6.1Long Short-Term Memory (LSTM)READING

Full Syllabus Gated (11+ Modules)

Unlock Full Curriculum & Labs

Enroll to unlock all 13 modules, 13 coding labs, automated graded quizzes, solution walk-throughs & verified certificate.

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Lead Instructor & Mentor

Instructor

Passionate engineer and educator specializing in core algorithms, production backend systems, and modern AI engineering.