CS X456.02 - AI Practicum (Project-based)

Course Description

This project-based course allows students to apply AI concepts and techniques in real-world scenarios by working on end-to-end AI solutions. Students will learn how to define project goals, prepare data, train models, implement retrieval-augmented generation (RAG), deploy their solutions, and present their work in a professional setting.

Learner Outcomes

Define and scope AI projects in alignment with real-world problems.
Apply data preparation techniques to project-specific datasets.
Train, validate, and fine-tune models, including large language models (LLMs).
Implement retrieval-augmented generation (RAG) to enhance AI models.
Deploy and monitor AI models in real-world applications.
Present AI project results effectively in a professional setting.

Prerequisites

CS X456.01 - Data and Data Preparation for AI (Pass)
CS X456 - Artificial Intelligence Principles: Deep Learning and Large Language Models (Pass)

Applies Towards the Following Certificates

Applied Artificial Intelligence : Required
Applied Artificial Intelligence : Required