Build LLM Applications Using Langchain and Flowise
About This Course
This WSQ Build LLM Applications Using Langchain and Flowise equips learners with the skills to identify opportunities for leveraging Large Language Models (LLMs) and assess their feasibility in business applications. Participants will integrate external data via OpenAI API and learn how to build dynamic LLM applications using both Langchain’s Python-based tools and Flowise’s intuitive low-code interface.
The course emphasizes testing and validating LLM workflows across disparate components using Langchain, as well as troubleshooting and modifying applications to ensure performance. With Flowise, learners will design and deploy LLM pipelines visually, accelerating development without deep coding. This course empowers learners to confidently create scalable, efficient AI solutions using both advanced and low-code tools.
What You'll Learn
- Identify Large Language Model (LLM) opportunities and perform feasibility scans.
- Utilise OpenAI API to integrate data and develop LLM applications.
- Peform tests in Langchain to verif LLM applications between disparate components and their functioning.
- Resolve technical issues in Langchain and implement modifications to LLM applications.
Course Outline:
Topic 1: Overview of Large Language Model (LLM)
• What is Large Language Model?
• Opportunities LLM applications
• Use cases of LLM applications
Topic 2 Building LLM Applications with OpenAI API
• OpenAI Prompt API
• Prompt Engineering and Chaining Prompts
• OpenAI Function Calling API
• Create a Chatbot with OpenAI API
Topic 3 LLM Application Development with LangChain
• Models, Prompts and Parsers
• Memory
• Chains
• Question and Answer
• Evaluation
• Agents
Topic 4 Data Integration with LangChain
• Document Loading and Splitting
• Vectorstores and Embedding
• Vector database
• Retrieval and Questioning/Answering
Entry Requirements
Knowledge and Skills
• Able to operate using computer functions
• 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: 21-65 years old.