Best first move
Pick one educator from the table, watch one matched video, then open one hands-on resource. The aim is to leave with a working habit, project, or mental model tied to production.
AI learning guide
Best AI resources for production AI engineering
Learn deployment, observability, latency, cost, MLOps, and product quality.
Quick answer
How to shortlist
Compare audience, level, format, and starting point. Favor a source that matches your current role and gives you exercises, examples, docs, or code you can use immediately.
What to avoid
Avoid collecting dozens of generic AI tips. Use this guide to choose a narrow learning loop: one topic, one educator, one video, one resource, one application in your own work.
Videos to watch
LLM evaluation with W&B
Weights & Biases
AI evals with Phoenix
Arize AI
AI Engineering with Chip Huyen
Chip Huyen
Full Stack Deep Learning lecture
Full Stack Deep Learning
MLOps community production AI
MLOps Community
ML Zoomcamp supervised learning
DataTalks.Club
Educators and sources
| Educator / source | Best for | Skills | Start with |
|---|---|---|---|
| Developers, AI engineers | AI engineering, Agents, Developer tools | Watch AI Engineer talks for production patterns and tool choices. | |
| Engineers, ML practitioners | AI engineering, Systems, Production ML | Use the book page and related essays as a production engineering path. | |
| Engineers shipping ML products | MLOps, Deployment, Product ML | Use the course modules that match your current project stage. | |
| Developers evaluating and deploying LLM apps | LLM apps, Evals, Experiment tracking, MLOps | Take Building LLM-powered apps, then the evaluation material. | |
| AI engineers and ML teams | Observability, Evals, Tracing, RAG debugging | Try Phoenix tracing on a small RAG or agent app. | |
| Teams shipping LLM applications | Observability, Prompt management, Evals, Tracing | Instrument a toy app with traces, then add scores and eval datasets. | |
| Engineers learning production ML | MLOps, Testing, Deployment, ML systems | Work through testing, monitoring, and deployment lessons. | |
| ML and AI engineers | MLOps, Production ML, AI systems, Community learning | Search talks for the system problem you are facing. | |
| Data and AI practitioners | Data systems, ML engineering, AI trends | Search episodes by topic: RAG, evaluation, agents, MLOps. | |
| Developers learning data and ML engineering | ML engineering, MLOps, Data engineering | Use ML Zoomcamp or MLOps Zoomcamp based on your gap. | |
| Developers and enterprise teams | Deep learning, GPU computing, Generative AI, Deployment | Pick a generative AI or accelerated computing workshop that matches your stack. | |
| Cloud developers and solution architects | Cloud AI, Agents, MLOps, Generative AI | Use an AI/ML learning plan tied to the AWS services you already use. | |
| Cloud developers and data teams | Cloud AI, Vertex AI, Generative AI, MLOps | Start with a generative AI or Vertex AI learning path. | |
| Developers deploying AI workloads | Deployment, GPU workloads, AI engineering, Batch jobs | Deploy a small inference example before moving a real workload. | |
| Developers building scalable vector search | Vector databases, RAG, Embeddings, Search | Work through a tutorial before designing your production index. | |
| Developers fine-tuning and deploying models | Open models, Fine-tuning, Deployment, Transformers | Pick one fine-tuning or inference guide and reproduce it end to end. | |
| Developers and data science learners | Machine learning, Deep learning, LLM apps, MLOps | Pick a playlist that matches your current level and follow the code. |
Resources
AI Engineering
Book · Chip Huyen · Intermediate to advanced
You are moving from demos to production systems.
W&B LLM Evaluation Course
Free course · Weights & Biases · Intermediate
You need to debug and measure LLM app quality.
Phoenix by Arize
Open source tool and docs · Arize AI · Intermediate
You need to trace, inspect, and evaluate LLM app behavior.
Langfuse Docs
Docs and cookbooks · Langfuse · Intermediate
You need production LLM tracing, scoring, and prompt operations.
Made With ML
Free course · Made With ML · Intermediate
You need production ML habits that transfer to AI systems.
DataTalks.Club ML Zoomcamp
Free cohort course · DataTalks.Club · Beginner to intermediate
You want a structured free path into ML engineering.
Full Stack Deep Learning Lectures
Course videos · Full Stack Deep Learning · Intermediate to advanced
You want the whole lifecycle of ML and AI product development.
AI Engineering
Book · Chip Huyen · Intermediate to advanced
Use this when you want Chip Huyen's material for ai engineering and related AI skills.
Full Stack Deep Learning
Course · Full Stack Deep Learning · Intermediate to advanced
Use this when you want Full Stack Deep Learning's material for mlops and related AI skills.
W&B Courses
Free courses · Weights & Biases · Intermediate
Use this when you want Weights & Biases's material for llm apps and related AI skills.
Phoenix
Docs · Arize AI · Intermediate
Use this when you want Arize AI's material for observability and related AI skills.
Langfuse Docs
Docs · Langfuse · Intermediate
Use this when you want Langfuse's material for observability and related AI skills.
Made With ML
Course · Made With ML · Intermediate
Use this when you want Made With ML's material for mlops and related AI skills.
MLOps Community
Talks · MLOps Community · Intermediate to advanced
Use this when you want MLOps Community's material for mlops and related AI skills.
DataTalks.Club ML Zoomcamp
Free courses · DataTalks.Club · Beginner to intermediate
Use this when you want DataTalks.Club's material for ml engineering and related AI skills.
NVIDIA DLI
Workshops · NVIDIA Deep Learning Institute · Beginner to advanced
Use this when you want NVIDIA Deep Learning Institute's material for deep learning and related AI skills.
Questions this guide answers
How do I ship AI systems reliably?
Use the educator table, videos, and resources above to compare options by topic fit, depth, and format. A good choice gives you a concrete next step: a course module, code example, video walkthrough, project, or workflow you can try today.
Which resources teach production AI engineering?
Use the educator table, videos, and resources above to compare options by topic fit, depth, and format. A good choice gives you a concrete next step: a course module, code example, video walkthrough, project, or workflow you can try today.
What should I learn after building a demo?
Use the educator table, videos, and resources above to compare options by topic fit, depth, and format. A good choice gives you a concrete next step: a course module, code example, video walkthrough, project, or workflow you can try today.