LangChain in Action: Develop LLM-Powered Applications

LangChain in Action: Develop LLM-Powered Applications

Course Overview Are you looking to gain a new in-demand skill from the comfort of your home? Well, look no …

LangChain in Action: Develop LLM-Powered Applications

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1 Year Access

Intermediate

3 Students

3 hours, 42 minutes

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Course Overview

Are you looking to gain a new in-demand skill from the comfort of your home? Well, look no further; you’ve come to the right place!

Our easy-to-follow LangChain in Action: Develop LLM-Powered Applications will provide you with all the deep knowledge and insight you need to know about this topic. This comprehensive course has been broken down into several manageable modules, which we believe will assist you to easily grasp each concept – from the fundamental to the more advanced aspects of the course.

Learn the most in-demand skills from the safety & comfort of your home. Enjoy the freedom to learn at your own comfortable pace and prepare yourself for the market of the future.

Learning Outcomes

Whether you are an aspiring professional or a complete beginner, this course will improve your expertise and boost your CV with key skills and an accredited certification attesting to your knowledge.

Entry Requirement

- This course is available to all learners of all academic backgrounds.
- Learners should be aged 16 or over to undertake the qualification.
- Some basic understanding of the English language and numeracy.

Certification

After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can, however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £29 or in PDF format at the cost of £19.

- PDF certificate’s turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days

Why choose us?

- - Affordable, engaging & high-quality e-learning study materials;
  - Tutorial videos/materials from the industry-leading experts;
  - Study in a user-friendly, advanced online learning platform;
  - Efficient exam systems for the assessment and instant result;
  - The UK & internationally recognised accredited qualification;
  - Access to course content on mobile, tablet or desktop from anywhere, anytime;
  - The benefit of career advancement opportunities;
  - 24/7 student support via email.

Career path

Develop Your Career Plan is a useful qualification to possess and would be beneficial for any related profession or industry.

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
Preparation
	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 OutputParsers	00:06:00
	LLMChain with multiple inputs	00:02:00
	SequentialChains	00:04:00
	RouterChains	00:04:00
Callbacks
	Callbacks	00:05:00
Memory
	Memory basics – ConversationBufferMemory	00:04:00
	ConversationSummaryMemory	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
	VectorStores and Retrievers	00:07:00
	RAG Service with FastAPI	00:05:00
Agents
	Agents Basics – LLMs learn to use tools	00:06:00
	Agents with a custom RAG-Tool	00:07:00
	ChatAgents	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 RecordManager	00:04:00
	Indexing Documents in practice	00:06:00
	Document Retrieval with PgVector	00:03:00
LangSmith
	Introduction to LangSmith (User Interface and Hub)	00:02:00
	LangSmith Projects	00:07:00
	LangSmith 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 LangChain Expression Language	00:01:00
	LCEL Part 1 – Pipes and OpenAI Function Calling	00:07:00
	LCEL – Part 2 – VectorStores, ItemGetter, Tools	00:06:00
	LCEL – Part 3 – Arbitrary Functions, Runnable Interface, Fallbacks	00:07:00

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LangChain in Action: Develop LLM-Powered Applications