6 Lessons
Intermediate to Deep Learning Engineer
★ 4.98
(3,900+ Engineers Enrolled)
Deep Learning & PyTorch Neural Networks Architecture
Autograd, CNNs, ResNet, LSTMs, Scaled Dot-Product Attention & Transformers
⏱️ 40 Hours
📖 6 Modules
⚡ 20 Interactive Lessons
🏆 Free Verified Certificate
Complete Track Curriculum & Modules
Step-by-step interactive lessons with live browser compilers & coding assignments.
20 Lessons
1
3 Lessons
Module 1: PyTorch Tensors, Autograd & Computational Graphs
01. PyTorch Tensor Architecture: Strides, Storage Buffers, Memory Layout (Contiguous vs Non-Contiguous)
⏱️ 45 mins
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⚡ Interactive Sandbox
02. Dynamic Computational Graphs & The PyTorch Autograd Engine (grad_fn, requires_grad, backward)
⏱️ 45 mins
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⚡ Interactive Sandbox
03. GPU Acceleration with CUDA: Tensor Device Placement (to("cuda")), CUDA Streams & Pinned Memory
⏱️ 45 mins
•
⚡ Interactive Sandbox
2
4 Lessons
Module 2: Multi-Layer Perceptrons (MLPs) & Custom Training Loops
04. Building Custom nn.Module Classes, Custom Parameters & Activation Functions (ReLU, GELU, Swish)
⏱️ 45 mins
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⚡ Interactive Sandbox
05. Custom Datasets & High-Performance DataLoaders (num_workers, collate_fn, pin_memory)
⏱️ 45 mins
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⚡ Interactive Sandbox
06. The Enterprise Training Loop: Forward Pass, Loss Computation, Zero Grad, Backward Pass & Optimizer Step
⏱️ 50 mins
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⚡ Interactive Sandbox
07. Neural Regularization Techniques: Dropout, Batch Normalization (BatchNorm1d) & Layer Normalization (LayerNorm)
⏱️ 45 mins
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⚡ Interactive Sandbox
3
3 Lessons
Module 3: Convolutional Neural Networks (CNNs) & Computer Vision Architecture
08. Convolutional Operations: Kernels, Filters, Strides, Padding & Feature Map Dilation
⏱️ 45 mins
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⚡ Interactive Sandbox
09. Modern CNN Architectures: Residual Connections (ResNet), Squeeze-and-Excitation & ConvNeXt
⏱️ 50 mins
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⚡ Interactive Sandbox
10. Transfer Learning & Vision Fine-Tuning with Torchvision Pretrained Models
⏱️ 45 mins
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⚡ Interactive Sandbox
4
3 Lessons
Module 4: Recurrent Architectures: RNNs, LSTMs & GRUs for Sequential Data
11. Sequential Modeling: Vanilla RNNs & The Vanishing / Exploding Gradient Problem
⏱️ 45 mins
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⚡ Interactive Sandbox
12. Long Short-Term Memory (LSTM) Networks: Forget Gate, Input Gate, Candidate State & Output Gate Math
⏱️ 50 mins
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⚡ Interactive Sandbox
13. Gated Recurrent Units (GRUs) & Bidirectional Sequence Processing in PyTorch
⏱️ 45 mins
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⚡ Interactive Sandbox
5
3 Lessons
Module 5: Modern Transformer Architecture from Scratch in PyTorch
14. Scaled Dot-Product Attention: Query, Key, Value Matrices & Attention Softmax Calculation
⏱️ 50 mins
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⚡ Interactive Sandbox
15. Multi-Head Attention (MHA) & Causal Masking Implementation from Scratch in Pure PyTorch
⏱️ 55 mins
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⚡ Interactive Sandbox
16. Building a Complete GPT-Style Decoder-Only Transformer Language Model from Scratch
⏱️ 60 mins
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⚡ Interactive Sandbox
6
4 Lessons
Module 6: PyTorch Distributed (DDP), Mixed Precision (AMP) & Model Checkpointing
17. Automatic Mixed Precision (torch.cuda.amp.autocast & GradScaler) for 2x Faster GPU Training
⏱️ 45 mins
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⚡ Interactive Sandbox
18. Distributed Data Parallel (DDP) Architecture: Multi-GPU Synchronization with torch.distributed
⏱️ 55 mins
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⚡ Interactive Sandbox
19. Robust Checkpointing: Saving State Dicts, Resuming Training & Early Stopping Callbacks
⏱️ 45 mins
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⚡ Interactive Sandbox
20. Model Export & Production Serialization: TorchScript (JIT Tracing), ONNX & TensorRT Compilation
⏱️ 50 mins
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⚡ Interactive Sandbox
Target Big Tech Roles
Google / Meta SDE-2
Senior Full-Stack Architect
Lead Backend Engineer
Skills You Will Master
- Production-Grade Clean Architecture
- V8 Internals, Memory Profiling & Leaks
- Time & Space Complexity Optimization
- Big Tech Behavioral & System Design Edge
Verified Digital Certificate
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⚡
Live Interactive Sandbox
Test real-time code without installing Node, Python or C++ locally. Instant output in browser!
Launch Code Sandbox (8-in-1)