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Your learning path

Pick how deep you want to go and how much time you have. Depth decides which articles; time decides only how long it takes.

Level
Expert
Articles
146
Reading time
193h
Weeks
77

That is 77 weeks at 3h per week. Raising your hours spreads the same material over less time — or drop to a lower target level to study fewer articles.

  1. Week 1

    2h
    1. 1
      ML Foundations1h
    2. 2
      ML Foundations1h

  2. Week 2

    2.3h
    1. 3
      ML Foundations1.25h
    2. 4
      ML Foundations1h

  3. Week 3

    3h
    1. 5
      ML Foundations1h
    2. 6
      ML Foundations1h
    3. 7
      ML Foundations1h

  4. Week 4

    2.6h
    1. 8
      ML Foundations1.25h
    2. 9
      ML Foundations1.25h

  5. Week 5

    3h
    1. 10
      ML Foundations1h
    2. 11
      ML Foundations1h
    3. 12
      ML Foundations1h

  6. Week 6

    2.8h
    1. 13
      Foundations1h
    2. 14
      Classic NLP0.75h
    3. 15
      Classic NLP1h

  7. Week 7

    2.8h
    1. 16
      Foundations1.5h
    2. 17
      Classic NLP1.25h

  8. Week 8

    2.6h
    1. 18
      Classic NLP1.25h
    2. 19
      Classic NLP1.25h

  9. Week 9

    2.6h
    1. 20
      Classic NLP1.25h
    2. 21
      Classic NLP1.25h

  10. Week 10

    2.3h
    1. 22
      Foundations1.25h
    2. 23
      Foundations1h

  11. Week 11

    2.3h
    1. 24
      Foundations1.25hVisual explainer
    2. 25
      Foundations1h

  12. Week 12

    2.8h
    1. 26
      Foundations1h
    2. 27
      Foundations1h
    3. 28
      Foundations0.75h

  13. Week 13

    2h
    1. 29
      Foundations1hVisual explainer
    2. 30
      Foundations1h

  14. Week 14

    2.5h
    1. 31
      Foundations1.5h
    2. 32
      Foundations1h

  15. Week 15

    3h
    1. 33
      Internals1h
    2. 34
      Internals2hVisual explainer

  16. Week 16

    2.5h
    1. 35
      Internals2.5hVisual explainer

  17. Week 17

    2.3h
    1. 36
      Internals1.25h
    2. 37
      Internals1h

  18. Week 18

    2.5h
    1. 38
      Internals1.5h
    2. 39
      Internals1h

  19. Week 19

    1h
    1. 40
      Internals1h

  20. Week 20

    3h
    1. 41
      Internals3hVisual explainer

  21. Week 21

    2.8h
    1. 42
      Classic NLP1.25h
    2. 43
      Internals1.5h

  22. Week 22

    2h
    1. 44
      Internals2hVisual explainer

  23. Week 23

    3h
    1. 45
      Internals1.5h
    2. 46
      Internals1.5h

  24. Week 24

    2.6h
    1. 47
      Prompting1.25h
    2. 48
      Prompting1.25h

  25. Week 25

    2.5h
    1. 49
      Prompting1.5hVisual explainer
    2. 50
      Prompting1h

  26. Week 26

    2h
    1. 51
      Prompting1h
    2. 52
      Prompting1h

  27. Week 27

    2.3h
    1. 53
      Prompting1.25h
    2. 54
      Prompting1h

  28. Week 28

    2.1h
    1. 55
      Prompting1.25h
    2. 56
      Prompting0.75h

  29. Week 29

    3h
    1. 57
      RAG1h
    2. 58
      RAG2hVisual explainer

  30. Week 30

    3h
    1. 59
      RAG1.5h
    2. 60
      RAG1.5h

  31. Week 31

    2.6h
    1. 61
      RAG1.25h
    2. 62
      RAG1.25h

  32. Week 32

    2.8h
    1. 63
      RAG1.5hVisual explainer
    2. 64
      Agents1.25h

  33. Week 33

    2h
    1. 65
      Agents2hVisual explainer

  34. Week 34

    2h
    1. 66
      Agents2hVisual explainer

  35. Week 35

    2.8h
    1. 67
      Agents1.25h
    2. 68
      Agents1.5h

  36. Week 36

    2.8h
    1. 69
      Agents1.5h
    2. 70
      Agents1.25h

  37. Week 37

    2.8h
    1. 71
      Agents1.5h
    2. 72
      Agents1.25h

  38. Week 38

    3h
    1. 73
      Application1.5h
    2. 74
      Application1.5h

  39. Week 39

    1.8h
    1. 75
      Application1.75h

  40. Week 40

    2.6h
    1. 76
      Application1.25h
    2. 77
      Application1.25h

  41. Week 41

    3h
    1. 78
      Application1h
    2. 79
      Evaluation1h
    3. 80
      Evaluation1h

  42. Week 42

    2.8h
    1. 81
      Evaluation1h
    2. 82
      Evaluation0.75h
    3. 83
      Evaluation1h

  43. Week 43

    2.3h
    1. 84
      Evaluation1h
    2. 85
      Evaluation1.25h

  44. Week 44

    2h
    1. 86
      Evaluation1h
    2. 87
      Evaluation1h

  45. Week 45

    2h
    1. 88
      Multimodal2hVisual explainer

  46. Week 46

    2h
    1. 89
      Multimodal2hVisual explainer

  47. Week 47

    2.8h
    1. 90
      Multimodal1.5h
    2. 91
      Multimodal1.25h

  48. Week 48

    2.8h
    1. 92
      Multimodal1.5h
    2. 93
      Multimodal1.25h

  49. Week 49

    3h
    1. 94
      Multimodal1.5h
    2. 95
      Multimodal1.5h

  50. Week 50

    2.8h
    1. 96
      Training and Adaptation1.5h
    2. 97
      Training and Adaptation1.25h

  51. Week 51

    2.8h
    1. 98
      Training and Adaptation1.25h
    2. 99
      Training and Adaptation1.5h

  52. Week 52

    2.3h
    1. 100
      Training and Adaptation1.25h
    2. 101
      Evaluation1h

  53. Week 53

    2.8h
    1. 102
      Training and Adaptation1.25h
    2. 103
      Training and Adaptation1.5h

  54. Week 54

    2.8h
    1. 104
      Training and Adaptation1h
    2. 105
      Training and Adaptation1.75h

  55. Week 55

    2.8h
    1. 106
      Training and Adaptation1.5h
    2. 107
      Training and Adaptation1.25h

  56. Week 56

    2.8h
    1. 108
      Training and Adaptation1.25h
    2. 109
      Advanced Architecture1.5h

  57. Week 57

    3h
    1. 110
      Advanced Architecture1.5h
    2. 111
      Advanced Architecture1.5h

  58. Week 58

    3h
    1. 112
      Advanced Architecture1.5h
    2. 113
      Advanced Architecture1.5h

  59. Week 59

    2.6h
    1. 114
      Advanced Architecture1.25h
    2. 115
      Advanced Architecture1.25h

  60. Week 60

    3h
    1. 116
      Advanced Architecture1.5h
    2. 117
      Advanced RAG1.5h

  61. Week 61

    1.3h
    1. 118
      Advanced RAG1.25h

  62. Week 62

    2h
    1. 119
      Advanced RAG2hVisual explainer

  63. Week 63

    3h
    1. 120
      Advanced RAG1.5hVisual explainer
    2. 121
      Advanced RAG1.5h

  64. Week 64

    3h
    1. 122
      Advanced RAG1.5hVisual explainer
    2. 123
      Advanced RAG1.5h

  65. Week 65

    3h
    1. 124
      Advanced Agents1.5h
    2. 125
      Advanced Agents1.5h

  66. Week 66

    3h
    1. 126
      Advanced Agents1.5h
    2. 127
      Advanced Agents1.5h

  67. Week 67

    2.8h
    1. 128
      Advanced Agents1.5h
    2. 129
      Advanced Agents1.25h

  68. Week 68

    1.8h
    1. 130
      Advanced Agents1.75h

  69. Week 69

    2.8h
    1. 131
      Security1.25h
    2. 132
      Security1.5h

  70. Week 70

    2.8h
    1. 133
      Security1.25h
    2. 134
      Security1.5h

  71. Week 71

    2.8h
    1. 135
      Security1.5h
    2. 136
      Security1.25h

  72. Week 72

    2.8h
    1. 137
      Security1.5h
    2. 138
      Production1.25h

  73. Week 73

    2.8h
    1. 139
      Production1.5h
    2. 140
      Production1.25h

  74. Week 74

    2.3h
    1. 141
      Production1h
    2. 142
      Production1.25h

  75. Week 75

    2.3h
    1. 143
      Evaluation1h
    2. 144
      Production1.25h

  76. Week 76

    1.5h
    1. 145
      Production1.5h

  77. Week 77

    1.8h
    1. 146
      Production1.75h
What Is Machine Learning?
How Data Becomes Numbers
What Is a Neural Network?
Weights and Biases
The Forward Pass
Activation Functions
Loss Functions
Gradient Descent
Backpropagation
Overfitting and Generalization
Probability for AI
Train, Validation, Test
What Is a Token in AI?
Classic Text Preprocessing
Bag of Words and N-grams
What Is an Embedding?
word2vec: Where Word Vectors Began
Recurrent Neural Networks
LSTM and GRU: Memory That Lasts
Sequence to Sequence and Encoder-Decoder
The Origin of Attention
Where Does the Vocabulary Come From?
What Is an LLM?
How Does an LLM Actually Write?
Base Models vs Chat Models
The Language Modeling Objective
Logits and Softmax
Perplexity: A Language Model's Intrinsic Measure
Temperature and Top-p, Explained
Training vs Inference
What Happens During Pretraining?
What Does "7B Parameters" Mean?
Decoding Strategies: Greedy Search and Beam Search
The Geometry of Meaning
How Does a Transformer Work?
Encoder, Decoder, and Encoder-Decoder Architectures
The Feed-Forward Network in a Transformer
Layers, Residuals, and Depth
Normalization Layers: LayerNorm and RMSNorm
The Output Projection: From Hidden State to Vocabulary Logits
Self-Attention, Explained Visually
Why Transformers Won
What Is a KV Cache?
Why Multiple Attention Heads?
How Does a Model Know Word Order?
Why Long Contexts Cost So Much
Why Do AI Models Hallucinate?
Prompt Basics
Making a Model Think Step by Step
What Is a Context Window?
Show, Don't Tell: Few-Shot Prompting
In-Context Learning: Why Few-Shot Works
Your Prompt Isn't Working. Now What?
Prompt Patterns and Anti-Patterns
Getting JSON Out of an LLM
What Is a System Prompt?
Why RAG Exists
How RAG Works, Step by Step
How to Split Documents for RAG
RAG or Fine-Tuning?
Why You Need a Reranker
What Is a Vector Database?
How Similarity Search Actually Works
What Is an AI Agent?
How Does Tool Calling Work?
The Agent Loop
Agent Architectures: From Rules to Autonomy
How Agents Fail
Writing Good Tool Definitions
What Is MCP?
Multi-Step Planning
The ReAct Pattern
Your First LLM API Call
How Do You Know It Works?
From Demo to Production
Which Model Should You Use?
Cutting Your API Bill
Why Responses Stream
The Bias-Variance Tradeoff
Why Evaluation Is Harder Than Training
Precision, Recall, F1, and Accuracy
The Confusion Matrix: Why Accuracy Deceives
Human Evaluation and Annotation Agreement
Regression Metrics: MSE, MAE, and R²
Retrieval and Ranking Metrics
ROC and AUC: Evaluation Without a Threshold
Text Generation Metrics: BLEU, ROUGE, METEOR
How Do Models See Images?
How Image Generation Works
Multimodal Embeddings
Contrastive Learning and CLIP
How Speech Recognition Works
How Text-to-Speech Works
Vision-Language Models
Document and OCR Understanding
How Fine-Tuning Actually Works
Model Distillation
Hyperparameter Tuning
LoRA and Parameter-Efficient Fine-Tuning
Reading Model Benchmarks
Benchmark Contamination and Goodhart's Law
Optimizers and Learning Rate
What Is Quantization?
Regularization: Dropout and Weight Decay
How Models Are Aligned
How Reasoning Models Work
Synthetic Data
Transfer Learning: Why Pretraining Reuses
Attention Variants: Sparse, Linear, and Sliding Window
How Embedding Models Are Trained
How Inference Serving Works
How Long Context Became Possible
Mixture of Experts
Merging and Combining Models
Speculative Decoding
State Space Models
Agentic RAG
Contextual Retrieval
GraphRAG
Hybrid Search
RAG over Images and Tables
Query Rewriting and Expansion
Evaluating RAG
Evaluating Agents
Agent Memory
Coding Agents
Computer-Use Agents
Context Engineering
Human-in-the-Loop Design
Multi-Agent Systems
Model Supply Chain Risk
Handling PII and Sensitive Data
AI Governance and Compliance
Prompt Injection
Jailbreaks and Guardrails
Content Moderation
Red-Teaming AI Systems
Latency Optimization
Observability for LLM Systems
Cost Monitoring and Attribution
Prompt Versioning
A/B Testing AI Features
Statistical Significance: Why One Comparison Deceives
Migrating Between Models
Reliability Patterns
Self-Hosting Models