Learning Roadmap

AI & Machine Learning

From ML fundamentals to neural networks and transformers — build a solid theoretical and practical understanding of modern AI systems.

5Courses

58Min Total

2Topics

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Machine Learning

Introduction to Machine Learning

Learn what machine learning is, why it matters, and how the three main learning paradigms — supervised, unsupervised, and reinforcement learning — work.

Beginner10 min

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Deep Learning

Neural Networks Explained

From the perceptron to deep networks — understand how neurons, layers, activation functions, backpropagation, and regularization fit together.

Intermediate12 min

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Deep Learning

Transformer Architecture

Understand the attention mechanism, encoder-decoder structure, positional encoding, and why Transformers power modern LLMs like GPT and BERT.

Intermediate14 min

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Machine Learning

Gradient Descent & Optimization

A deep dive into gradient descent variants, adaptive optimizers (Adam, RMSProp), learning rate schedules, and practical tips for stable training.

Intermediate12 min

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Machine Learning

Overfitting & Regularization

Understand why models overfit, how to detect it, and which regularization techniques (dropout, L1/L2, early stopping, data augmentation) prevent it.

Beginner10 min

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