Generative AI and Large Language Models

This Coursera course places language models within a broader generative-AI sequence. Transformer architecture and practical LLM applications sit alongside diffusion and multimodal methods. It suits learners who want to compare model families rather than focus only on a chatbot framework.

What you will learn

• Explain transformer-based language models.
• Compare language, diffusion and multimodal generation approaches.
• Identify practical development steps for a generative application.

Who this suits

Intermediate learners familiar with Python syntax, data structures and linear algebra, including vectors, matrices and related operations.

Before you enroll

Preview the exact tools and model versions in the exercises. Hosted APIs, local models and experiment-tracking services have different setup and access requirements.

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Put it into practice

Compare a text-only and a multimodal task. Describe what data each needs and propose a separate evaluation method for the usefulness and correctness of their outputs.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

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