Generative AI and LLM Foundations

Not for most of it. Eight modules are concepts you can follow with no code at all. The API, Ollama and project modules use short Python snippets that are given to you; if you have never coded, do the Python for AI course alongside.

No. The course uses OpenRouter's free models, which need only a free key and no card. It uses Ollama for local models, which is free and runs on your own machine.

You build the simplest assistant that answers questions from three public datasheets on a free model. Then you test it with fifteen questions you have verified yourself, including five it cannot know. You report its accuracy and how often it invents an answer. A second, shorter project compares a hosted model with a local one.

Yes. Every module, practice task, project and assessment. You create an account so your progress is saved and the assessments can be marked. The certificate is the only paid item, and only if you want it.

An EDWartens Certificate of Completion, issued when you have finished the modules and passed the final assessment (the project is optional practice), with a verification code anyone can check. It is not a vendor credential and is never described as one.

The creators named in the Credits block at the foot of this page, on their own YouTube channels. EDWartens did not make the videos and the creators are not affiliated with EDWartens. What EDWartens wrote is the study plan, the notes, the practice tasks, the projects and the assessments.

Plan on about 16 hours in all, including the video lessons, notes and practice tasks. It is self-paced, so you work through the thirteen modules at your own speed.

No. The lab is optional practice. You can skip it whenever you like, and it never blocks your progress, the final assessment or your certificate.

Yes. Every lab level for this course opens in your browser, free, with nothing to install.

The Generative AI and LLM Foundations course has 13 modules. It opens with "What generative AI is, and what it is not", goes through "How an LLM works: tokens in, probabilities out", "Using it responsibly in a plant", "Embeddings, vector search and the idea of RAG" and "The datasheet assistant, tested" and ends with "Final assessment". The full list with minutes is under "What you learn" on this page.

After the Generative AI and LLM Foundations course: Explain in plain words what an LLM does when it answers, and why it hallucinates; Choose a model for a job: context length, JSON output, local or hosted, licence; Write a prompt with role, task, context, format and a NOT FOUND rule. These are the practical outcomes the course is written around, and the final assessment of 15 questions checks them.

For the Generative AI and LLM Foundations course, software: Google Colab, a free OpenRouter key, optionally Ollama on your own laptop. No paid account anywhere. Hardware: none required. A laptop with 8 GB RAM runs the optional local models. The course itself is free.

Generative AI and LLM Foundations is rated beginner. Beginner. No coding needed for eight of the twelve modules; basic Python (the Python for AI course, or equivalent) for the API and project modules. It is written for engineers, developers and students applying AI to real work, and takes about 16.5 hours at your own pace.

Skills from the Generative AI and LLM Foundations course (for example: explain in plain words what an LLM does when it answers, and why it hallucinates) are used in roles such as AI engineer, machine learning engineer, data analyst and automation developer, and in machine learning engineer work. The course gives you practical evidence of the skill; it does not promise a job, and employers decide on experience and interview.