Application Development with LLMs

Prerequisite: Introduction to Generative AI with Python and LLMs

Application Development with LLMs is the second required course in Villanova’s Generative AI Certificate. Building on the foundational Python and LLM concepts introduced in Introduction to Generative AI with Python and LLMs, this course helps learners move from foundational AI fluency into practical application development.

Learners explore how large language models can be integrated into Python applications using APIs, structured prompting and multi-step prompt workflows. The course also introduces embeddings, basic vector search and retrieval-augmented generation, or RAG, helping learners understand how AI applications can draw from external information to produce more useful and context-aware responses.

Throughout the course, learners practice building, testing and troubleshooting AI-powered applications with support from LLM-assisted coding tools. The course also emphasizes trust, responsibility and observability, helping learners better understand how LLM systems behave, where they can fail and how to evaluate their outputs more effectively.

What You'll Learn in This Course

By the end of the course, learners should be able to:

• Integrate LLMs into Python applications using APIs and structured prompting
• Design multi-step prompt workflows, also known as prompt chaining, for task automation
• Apply AI-assisted coding techniques to build, test and troubleshoot AI-powered applications
• Use embeddings and basic vector search to build introductory RAG applications
• Explore observability practices that help diagnose system behavior and application failures
• Evaluate LLM-powered applications with attention to trust, reliability and responsible use

Do You Need Prior Experience?

This course builds directly on Introduction to Generative AI with Python and LLMs, which is the prerequisite for enrollment.

Learners should have foundational familiarity with Python, prompting and basic LLM concepts before beginning this course. Advanced software development experience is not required, but learners should be prepared to work hands-on with coding environments, APIs and guided application-building exercises.

Course Specifics

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