Develop LLM Applications with LangChain

Multiday, 22/02/2025 - 23/02/2025

Venue

Tertiary Courses Malaysia G-3A-02, Suite Pejabat Korporat, KL Gateway, No 2, Jalan kerinchi, Gerbang kernichi Lestari, 59200

Entrance Fee

MYR2,000.00

Category

Business & Professional

Event Type

Class, Course, Training or Workshop

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Schedule

DateTime
22/02/20259:30 AM - 5:30 PM
23/02/20259:30 AM - 5:30 PM
Develop LLM Applications with LangChain

Our LangChain courses offer a deep dive into the intriguing world of Large Language Models (LLMs), empowering learners to develop robust AI applications that can understand, interpret, and generate human-like text. Whether you're a seasoned AI practitioner or a newcomer to the field, our comprehensive courses are designed to equip you with the advanced skills needed to harness the full potential of LLMs.

The curriculum focuses on understanding the fundamental mechanics of LLMs, exploring their wide-ranging applications, and learning how to effectively implement them in a variety of contexts. From mastering the nuances of NLP to fine-tuning LLMs for specific tasks, learners will be exposed to a wealth of knowledge that includes both theory and practical aspects. By the end of our LangChain courses, you will be proficient in building AI applications that can meaningfully interact with LLMs, creating more value in your projects and offerings.

Certificate

All participants will receive a Certificate of Completion from Tertiary Courses after achieved at least 75% attendance.

Funding and Grant

HRD Corp Claimable Course for Employers Registered with HRD Corp

HRDF claimable

Course Code: M784

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  Retrieval Augmented Generation (RAG) with LangChain

  • Overview of RAG

  • Document Loading and Splitting 

  • Text Embedding

  • Vector Stores 

  • Retrieval and Questioning/Answering