GenAI Deployment and Capstone (Part of SCTP)
About This Course
This course is the final, project-focused stage of the AI Engineering programme. Learners will explore the architecture of modern AI systems, focusing on Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). They will applythese concepts directly by building a functional RAG chatbot using vector databases and industry-standard AI frameworks. The objective is to synthesize all skills learned throughout the programme—from frontend and backend development to DevOps—into a single, comprehensive capstone project.
By the end, learners will have independently planned, developed, and deployed a complete, AI-powered application, creating a portfolio piece that showcases their readiness for complex engineering roles in the AI industry.
What You'll Learn
Articulate the fundamental concepts behind Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, and vector search to inform the design of intelligent applications.
Develop and integrate a functional Retrieval-Augmented Generation (RAG) chatbotinto a full-stack application using modern AI frameworks and vector databases.
Evaluate and utilize various generative AI tools, frameworks, and platforms to rapidly prototype and build proof-of-concept AI-driven features.
Independently scope, plan, develop, and deploy a substantial capstone project that solves a real-world problem by integrating custom software engineering with generative AI technologies.
Demonstrate a comprehensive ability to combine principles from software engineering, frontend/backend development, and DevOps to successfully deploy a complete, scalable AI-powered application.
Entry Requirements
Able to code in at least one programming language and Git for version control, ata basic to intermediate level. At least an understanding of and ability to code programming fundamentals.
Applicants will be required to undergo a shortlisting process where they must share their résumé and complete a pre-course assessment. Our instructors and careerconsultants will review applicants to assess their suitability before deciding whether to shortlist them for the course.