LangChain in Action: Develop LLM-Powered Applications

LangChain in Action: Develop LLM-Powered Applications

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Empower your career journey with our in-demand course: LangChain in Action: Develop LLM-Powered Applications

Boost your proficiency and propel your career forward with our meticulously crafted course, designed to be your ultimate guide to professional development. Our super-accessible modules break down complex topics into bite-sized, easy-to-understand lessons, filling your knowledge gaps and equipping you with real-world, practical skills.

Seeking career advancement and application of your skills? You’ve found the right place. This LangChain in Action: Develop LLM-Powered Applications is your exclusive passport to unlocking your full potential.

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Course design

The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace.

You are taught through a combination of

Exam & Retakes

It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable.


Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery).

Course Curriculum

Before we start
Why this course is different 00:01:00
Prerequisites 00:01:00
Essential topics and terms (theory) 00:04:00
Why this course does not cover Open Source models like LLama2 00:01:00
Optional: Install Visual Studio Code 00:02:00
Get the source files with Git from Github 00:02:00
Create OpenAI Account and create API Key 00:02:00
Setup of a virtual environment 00:03:00
Setup OpenAI Api-Key as environment variable 00:03:00
Exploring the vanilla OpenAI package 00:03:00
LangChain Basics
LLM Basics 00:07:00
Prompting Basics 00:02:00
Theory: Prompt Engineering Basics 00:02:00
Few Shot Prompting 00:05:00
Chain of thought prompting 00:02:00
Pipeline-Prompts 00:04:00
Prompt Serialisation 00:03:00
Chains - From basic to advanced chains
Introduction to chains 00:01:00
Basic chains – the LLMChain 00:03:00
Response Schemas and Output Parsers 00:06:00
LLMChain with multiple inputs 00:02:00
Sequential Chains 00:04:00
Router Chains 00:04:00
Call backs 00:05:00
Memory basics – Conversation Buffer Memory 00:04:00
Conversation Summary Memory 00:03:00
EXERCISE: Use Memory to build a streamlit Chatbot 00:01:00
SOLUTION: Chatbot with Streamlit 00:03:00
OpenAI Function Calling
OpenAI Function Calling – Vanilla OpenAI Package 00:08:00
Function Calling with LangChain 00:04:00
Limits and issues of the langchain Implementation 00:03:00
Retrieval Augmented Generation (RAG)
RAG – Theory and building blocks 00:03:00
Loaders and Splitters 00:04:00
Embeddings – Theory and practice 00:04:00
Vector Stores and Retrievers 00:07:00
RAG Service with Fast API 00:05:00
Agents Basics – LLMs learn to use tools 00:06:00
Agents with a custom RAG-Tool 00:07:00
Chat Agents 00:03:00
Indexing API
Indexing API – keep your documents in sync 00:02:00
PREREQUISITE: Docker Installation 00:01:00
Setup of PgVector and Record Manager 00:04:00
Indexing Documents in practice 00:06:00
Document Retrieval with PgVector 00:03:00
Introduction to Lang Smith (User Interface and Hub) 00:02:00
Lang Smith Projects 00:07:00
Lang Smith Datasets and Evaluation 00:13:00
Microservice Architecture for LLM Applications
Introduction to Microservice Architecture 00:04:00
How our Chatbot works in a Microservice Architecture 00:02:00
Introduction to Docker 00:05:00
Introduction to Kubernetes 00:02:00
Deployment of the LLM Microservices to Kubernetes 00:13:00
LangChain Expression Language (LCEL)
Intro to Lang Chain Expression Language 00:01:00
LCEL Part 1 – Pipes and OpenAI Function Calling 00:07:00
LCEL – Part 2 – Vector Stores, Item Getter, Tools 00:06:00
LCEL – Part 3 – Arbitrary Functions, Runnable Interface, Fallbacks 00:07:00

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