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Learning Paths

LLMs & Agents

Prompting, RAG pipelines, and agentic workflows.

Infrastructure & Systems

Hardware sizing, local deployment, and quantization.

Deep Learning & PyTorch

Neural architectures, PyTorch, Transformers, and RL.

Core Foundations

Python, linear algebra, calculus, and classical ML.

All Courses

Full catalog ordered by prerequisite sequence.

Deep Learning & PyTorch

Neural architectures, PyTorch, Transformers, and RL.

Deep Learning Foundation

Forward-backward propagation, loss landscapes, optimization algorithms, and neural networks.

4 Courses

1

Calculus Fundamentals for Machine Learning

Foundational

2

Introduction to Neural Networks

Intermediate

3

Introduction to Deep Learning

Intermediate

4

Deep Learning Fundamentals with Keras

Intermediate

Advanced PyTorch Engineering

Custom autograd functions, mixed-precision training (AMP), DistributedDataParallel (DDP), and FSDP.

3 Courses

1

Advanced PyTorch

Specialist

2

Distributed Training of Large Models with PyTorch FSDP

Expert

3

Advanced Compiler and Runtime Optimizations for ML Workloads

Expert

Multimodal AI Developer

Vision-language architectures, cross-attention projection, CLIP embeddings, and multimodal pipelines.

4 Courses

1

Introduction to Computer Vision

Foundational

2

Natural Language Processing Fundamentals

Intermediate

3

Introduction to Speech Recognition

Foundational

4

Introduction to Multimodal AI

Foundational

Advanced Diffusion Models

Score-based generative models, DDPM/DDIM samplers, latent diffusion architectures, and conditioning mechanisms.

3 Courses

1

Introduction to Diffusion Models for Generative AI

Intermediate

2

Advanced Diffusion Model Architectures and Training

Specialist

3

Deploying Diffusion Models at Scale

Specialist

Applied Reinforcement Learning

Markov decision processes, policy gradients (PPO), value estimation, and reward model training.

4 Courses

1

Introduction to Reinforcement Learning

Intermediate

2

Intermediate Reinforcement Learning Techniques

Intermediate

3

Advanced Reinforcement Learning Techniques

Specialist

4

RLHF: Reinforcement Learning from Human Feedback

Specialist

Mixture of Experts (MoE) Specialist

Sparse routing algorithms, expert capacity factor, load balancing loss, and distributed expert parallelism.

3 Courses

1

Introduction to Transformer Models

Intermediate

2

Mixture of Experts: Core Concepts and Hands-on Implementation

Specialist

3

Mixture of Experts: Advanced Architecture, Training, and Scaling

Expert

Audio and Speech AI

Acoustic feature extraction, spectrograms, Whisper ASR architecture, and neural audio synthesis.

3 Courses

1

Introduction to Speech Recognition

Foundational

2

Applied Speech Recognition

Intermediate

3

Advanced Speech Recognition and Synthesis

Specialist

Deep Learning Optimization

Hardware profiling, memory footprint reduction, gradient checkpointing, and FlashAttention.

3 Courses

1

Model Regularization and Optimization in Deep Learning

Intermediate

2

Advanced Optimization Techniques for Machine Learning

Specialist

3

Advanced PyTorch

Specialist

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