Onlayn kurslar

Bepul (eng yaxshilari)

Klassik ML

• Andrew Ng — Machine Learning Specialization(Coursera)

• 3 kurs: Supervised, Advanced Learning, Unsupervised

• Bepul auditing(sertifikat $50)

• Boshlovchilar uchun #1

• fast.ai — Practical Deep Learning for Coders(free)

• Top-down approach (kodlash → matematika)

• course.fast.ai

• CS229 — Stanford ML(YouTube)

• Mathematical foundation

• Andrew Ng yoki Anand Avati

Deep Learning

• Andrew Ng — Deep Learning Specialization(Coursera, free auditing)

• 5 kurs: NN, Improving, ML projects, CNN, Sequence models

• CS231n — Stanford CNN(YouTube)

• Computer Vision deep dive

• Lecture'lar 2017'dan, lekin hali ham aktual

• MIT 6.S191 — Intro to Deep Learning(YouTube)

• Har yili yangilanadigan

• introtodeeplearning.com

NLP / LLM

• HuggingFace NLP Course(free) — MUST DO

• HuggingFace ekosistemasini o'rgatadi

• huggingface.co/learn/nlp-course

• CS224n — Stanford NLP with Deep Learning(YouTube)

• Christopher Manning

• DeepLearning.AI Short Courses(free)

• LangChain, RAG, Agents, Fine-tuning

• learn.deeplearning.ai

MLOps

• MLOps Zoomcamp — DataTalks.Club(free, GitHub) — MUST DO

• Eng yaxshi MLOps kursi

• github.com/DataTalksClub/mlops-zoomcamp

• Made With ML — Goku Mohandas(free)

• Production ML patterns

• madewithml.com

• Full Stack Deep Learning(Berkeley, free)

• End-to-end ML systems

• fullstackdeeplearning.com

Data Engineering

• Data Engineering Zoomcamp — DataTalks.Club (free, GitHub)

• DE for ML engineers

• Andrej Karpathy — Neural Networks: Zero to Hero(YouTube)

• GPT'ni noldan qurish

Specialized

• CS25 — Transformers United(Stanford, YouTube)

• Transformers deep dive

• Andrew Ng — Generative AI for Everyone(Coursera, free)

• Non-technical, lekin yaxshi overview

Pullik (qiymatga arziydi)

Coursera Specializations ($49/oy)

• Andrew Ng — ML Specialization+ sertifikat
• Andrew Ng — DL Specialization+ sertifikat
• MLOps Specialization — DeepLearning.AI
• TensorFlow Developer Certificate

Educative.io

• Grokking the ML Interview — interview prep
• Grokking the System Design Interview

Udacity Nanodegrees ($$$)

• ML Engineer Nanodegree
• AI Programming with Python

Wandb Courses (free!)

• W&B Effective ML Workflows
• LLM Engineering Practices
• wandb.courses

🎯 Yo'lingiz uchun tavsiya tartibi

Oy 1-2 (Foundations + Classical ML)

1. Andrew Ng — ML Specialization(Coursera) — asoslar
2. fast.ai Part 1(parallel) — praktik
3. Wes McKinney book — Pandas

Oy 3 (Deep Learning)

1. Andrew Ng — DL Specialization — theory
2. fast.ai Part 2 — praktik
3. CS231n(rasm bilan ishlasangiz) — vision

Oy 4 (CV + NLP)

1. HuggingFace NLP Course — transformers
2. CS224n — NLP theory
3. Ultralytics YOLO docs — practical CV

Oy 5 (LLM + RAG)

1. DeepLearning.AI Short Courses(8-10 ta)
2. HuggingFace Course(LLM section)
3. Karpathy — Zero to Hero — chuqurroq

Oy 6 (MLOps)

1. MLOps Zoomcamp — boshidan oxirigacha
2. Made With ML — production patterns
3. Full Stack DL — system design

Kurslarni qanday samarali ishlatish

O'rganish strategiyasi

1. Lecture'larni 1.5x speed — vaqt tejash
2. Notes — alohida markdown faylda
3. Assignment'larni qiling — passive watching kifoya emas
4. Project — kursdan keyin o'z loyihangiz
5. Forum — Discord/Slack/Coursera forum'larida qatnashing

Vakt taqsimoti (kuniga 1-2 soat)

• 30-45 min — yangi material (kurs lecture)
• 30-45 min — practice (kod yozish, kitob o'qish)
• 15-30 min — review (eski material, flashcards)

Sertifikatlar — kerakmi?

• Kompaniya talab qilsa — ha
• CV'ni boyitish — yaxshi, lekin loyiha muhimroq
• O'z bilimini sinash — bepul auditing ham yetadi
• Mahalliy bozor — Coursera sertifikatlari hurmatga ega

**Maslahat:**Sertifikatdan ko'ra GitHub portfoliomuhimroq.

Bootcamps (intensive)

Bepul

• MLOps Zoomcamp(DataTalks.Club) — 9 hafta
• Made With ML — self-paced

Pullik ($$$$)

• Le Wagon Data Science — 9-24 hafta
• DataCamp Career Track
• Springboard ML Engineer Track(mentor bilan)

Universiteti darajasidagi kurslar (free YouTube)

YouTube kanallar ga o'tish.