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Strengths
- Ng Enda teaches in person, the content is authoritative and systematic
- There are tons of free courses available so you can learn without paying
- Short courses (1-2 hours) to quickly learn the latest AI technology
- Official courses in partnership with OpenAI, Google, AWS, and more
- Chinese subtitle support, suitable for Chinese learners
Best for
- System learning machine learning and deep learning basics
- Quickly learn about the latest AI technologies (Prompt Engineering, RAG, etc.)
- Get your Coursera certification
- Learn LLM application development
- Technical Literacy for AI Product Managers
Recommended learning path
Choose the appropriate learning path based on your background and goals.
Scenario
The entry path for AI beginners
Prompt example
Recommended learning order: Step One: AI For Everyone (Free) - For non-technical people - Understand the basic concepts and applications of AI - about 6 hours Step Two: Machine Learning Specialization (Free Audition) - Andrew Ng Classics Course, in partnership with Stanford - Supervised learning, unsupervised learning, reinforcement learning - Approximately 3 months (10 hours per week) Step Three: Deep Learning Specialization (Free Audition) - Neural network, CNN, RNN, Transformer - about 5 months
Output / what to expect
After completing these three courses,
You will have a solid theoretical foundation in AI/ML,
Ability to understand mainstream AI papers and technical articles.
Tips
Select "Audit" on Coursera to study all videos for free, only the certificates require payment.
Scenario
Fast path for LLM application developers
Prompt example
If you already have a programming foundation and want to quickly learn LLM application development: Short courses (1-2 hours each, all free): 1. ChatGPT Prompt Engineering for Developers - Learn how to write prompts well - Partnering with OpenAI 2. Building Systems with the ChatGPT API - Build multi-step AI systems 3. LangChain for LLM Application Development - Learn LangChain framework 4. Building and Evaluating Advanced RAG - Advanced RAG technology 5. Finetuning Large Language Models - Getting started with model fine-tuning
Output / what to expect
These 5 short courses last approximately 10 hours,
After completing the course, you can independently develop LLM applications.
All free and of extremely high quality.
Tips
Short Courses are a feature of DeepLearning.AI. You can learn a practical technical point in 1-2 hours.