Develop Artificial Intelligence and Large Language Model (LLM) Applications with Google Gemini
About This Course
Master the development of advanced Artificial Intelligence (AI) solutions by leveraging the power of Google Gemini's Large Language Models (LLMs). This course begins with a comprehensive overview of LLMs, their industrial use cases, and introduces you to Google Gemini. Explore multimodal prompting through Google AI Studio and Vertex AI, gaining practical experience with workflows that integrate Gemini's capabilities.
Dive deeper into building LLM-driven applications using Langchain and Gemini, automating workflows and creating intelligent AI agents. Additionally, learn how to implement Retrieval Augmented Generation (RAG) technology by managing document embedding, splitting, and utilizing vector databases. This course equips you with the skills to design, develop, and evaluate LLM applications for real-world deployment.
What You'll Learn
LO1: Analyze the range of LLM applications using Generative AI (GAI) and identify their industrial use cases.
LO2 Establish Google Gemini GAI designs and assess improvements on engineering processes.
LO3 Develop LLM applications and assess its feasibility
LO4 Evaluate the performance effectiveness of Retrieval Augmented Generation (RAG)
Topics Covered:
Topic 1: Overview of Large Language Model (LLM)
What is Large Language Model?
Use cases of LLM applications
Introduction to Gemini LLM
Topic 2: Multimodal Prompting with Gemini Pro LLM
Introduction to Google AI Studio
What is Multimodal Prompting
Multimodal Prompting with Google API Key
Introduction to Vertex AI
Multimodal Prompting with Vertex AI
Topic 3: Building LLM Applications with Google Gemini LLM
Overview of Langchan Components
Automate Workflow with Langchain and Gemin Model
Create AI Agent Using Langchain and Gemini LLM Model
Topic 4: Implementing Retrieval Augmented Generation (RAG)
Overview of LLM driven RAG technology
Document Loading and Splitting
Embedding
Vector Databases
RAG implementation
Entry Requirements
Knowledge and Skills
• Able to operate computer functions with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
• Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)
Attitude
• Positive Learning Attitude
• Enthusiastic Learner
Experience
• Minimum of 1 year of working experience.
Target Age Group: 21 to 65 years old