1. Kirish
  2. Muallif haqida
  4. Oy 1 — Foundations (Asoslar)
  5. Umumiy ko'rinish
  6. Matematika asoslari
  7. NumPy
  8. Pandas
  9. Matplotlib va Seaborn
  10. EDA loyihasi (Capstone)
  11. Mashqlar
  13. Oy 2 — Klassik ML (Scikit-learn)
  14. Umumiy ko'rinish
  15. ML ga kirish
  16. Regression
  17. Classification
  18. Clustering
  19. Feature Engineering
  20. Model Evaluation
  21. Ensemble Methods (XGBoost, LightGBM)
  22. Mashqlar
  24. Oy 3 — Deep Learning
  25. Umumiy ko'rinish
  26. Neural Networks asoslari
  27. PyTorch asoslari
  28. TensorFlow va Keras
  29. Training texnikalari
  30. CNN — Convolutional Networks
  31. RNN, LSTM, GRU
  32. Mashqlar
  34. Oy 4 — Computer Vision + NLP
  35. Umumiy ko'rinish
  36. Computer Vision ga kirish
  37. OpenCV bilan ishlash
  38. YOLO va Object Detection
  39. NLP asoslari
  40. Text Preprocessing
  41. Transformers ga kirish
  42. Mashqlar
  44. Oy 5 — LLM, RAG va AI Agentlar
  45. Umumiy ko'rinish
  46. LLM fundamentals
  47. Prompt Engineering
  48. OpenAI va Anthropic API
  49. LangChain va LlamaIndex
  50. Vector Databases
  51. RAG Pipeline
  52. AI Agents
  53. Fine-tuning (LoRA, QLoRA)
  54. Mashqlar
  56. Oy 6 — MLOps va Production
  57. Umumiy ko'rinish
  58. MLOps ga kirish
  59. MLflow — Experiment tracking
  60. DVC — Data Versioning
  61. FastAPI + ML Serving
  62. Docker va Kubernetes
  63. Model Monitoring
  64. CI/CD for ML
  65. Airflow va Prefect
  66. Mashqlar
  68. Final Loyihalar
  69. Portfolio loyihalar
  70. 1. Prediction API (Klassik ML + FastAPI)
  71. 2. Computer Vision Service
  72. 3. RAG Chatbot
  73. 4. MLOps Pipeline (End-to-End)
  75. Resurslar
  76. Resurslar ro'yxati
  77. Kitoblar
  78. Onlayn kurslar
  79. YouTube kanallar
  80. Datasets
  81. Cheatsheets
  84. Glossary (Lug'at)