LangChain with Python Bootcamp

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Jose Portilla

5:59:44

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1. Introduction

1. Introduction.html

2. Models - Input and Outputs

1. Introduction to Models - Inputs and Outputs.mp4

04:27

2. Using LLMs with LangChain.mp4

16:29

3. Chat Models with LangChain.mp4

16:26

4. Prompt Templates.mp4

17:50

5. Prompt and Models - Exercise.mp4

02:20

6. Prompt and Models - Exercise Solution.mp4

06:37

7. Few Shot Prompt Template.mp4

10:28

8. Parsing Output - Part One.mp4

14:30

9. Parsing Output - Part Two.mp4

12:05

10. Parsing Output - Part Three.mp4

08:10

11. Serialization -Saving and Loading Prompts.mp4

02:30

12. Models - Inputs and Outputs - Project Exercise.mp4

05:12

13. Models - Inputs and Outputs - Project Exercise Solution.mp4

19:46

3. Data Connections

1. Introduction to Data Connections.mp4

00:50

2. Document Loaders - Part One.mp4

13:24

3. Document Loaders - Integrations.mp4

08:57

4. Document Loading Exercise.mp4

03:32

5. Document Loading Exercise - Solution.mp4

07:15

6. Document Transformers.mp4

11:04

7. Text Embedding.mp4

07:36

8. Vector Store.mp4

20:27

9. Vector Store - Retrievers.mp4

02:37

10. MultiQuery Retrieval.mp4

13:36

11. Context Compression.mp4

10:36

12. Data Connections Exercise.mp4

01:35

13. Data Connections Exercise - Solutions.mp4

05:32

4. Chains

1. Introduction to LangChain Chains.mp4

01:42

2. LLMChain Object.mp4

05:32

3. SimpleSequentialChain.mp4

10:21

4. SequentialChain.mp4

12:15

5. LLMRouterChain.mp4

23:11

6. TransformChain.mp4

08:46

7. OpenAI Function Calling with LangChain.mp4

10:04

8. MathChain.mp4

04:30

9. Additional Chains - QA Documents.mp4

09:21

10. Chains - Exercise.mp4

02:09

11. Chains - Exercise Solution.mp4

07:21

5. Memory

1. Introduction to Memory.mp4

01:48

2. ChatMessageHistory Object.mp4

03:05

3. ConversationBufferMemory.mp4

07:58

4. ConversationBufferWindowMemory.mp4

04:11

5. ConversationSummaryMemory.mp4

03:39

Description

Build real world applications with Large Language Models and LangChain!

What You'll Learn?

Learn to use LangChain for Model Inputs and Outputs to easily switch out LLMs.
Discover how to perform data connections with Vector Databases such as ChromaDB with your LLMs and Langchain.
Understand how to utilize LangChain memory to keep track of User and AI conversations.
Use LangChain to build out custom agents to accomplish tasks with LLMs.

Who is this for?

Python developers interested in using LangChain to develop LLM Applications

What You Need to Know?

Python Programming Experience Required, recommended you also have familiarity with OpenAI

More details

Description
Welcome to the LangChain Udemy course: Unlock the Power of Language Models with Python!
Ready to develop cutting-edge applications powered by language models? LangChain is the framework you need. With LangChain, create data-aware and agentic applications that connect language models with other data sources and enable interaction with the environment.
Why Choose LangChain?
LangChain offers numerous benefits for your language model development needs:
Components: LangChain provides modular and user-friendly abstractions for working with language models, along with a wide range of implementations.
Off-the-shelf chains: Start building applications quickly with pre-built chains designed for specific tasks. Modify existing chains or create new ones for more complex or customized use-cases.
LangChain Course Modules:
LangChain offers standard interfaces and external integrations for various modules:
Model I/O: Easily interface with language models.
Data connection: Connect with application-specific data sources.
Chains: Construct sequences of calls to accomplish specific tasks.
Agents: Enable chains to choose tools based on high-level directives.
Memory: Persist application state between runs of a chain.
With LangChain you'll be able to quickly build real world applications that directly sync up with Large Language Models, such as OpenAI's GPT-4 API!
Revolutionize your applications with the power of language models. Enroll in our LangChain Udemy course now and unlock limitless possibilities!
Who this course is for:
Python developers interested in using LangChain to develop LLM Applications

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Python

Jose Portilla

Instructor's Courses

Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University and years of experience as a professional instructor and trainer for Data Science, Machine Learning and Python Programming. He has publications and patents in various fields such as microfluidics, materials science, and data science. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data science to help other people learn the power of programming, the ability to analyze data, and the skills needed to present the data in clear and beautiful visualizations. Currently he works as the Head of Data Science for Pierian Training and provides in-person data science and python programming training courses to employees working at top companies, including General Electric, Cigna, The New York Times, Credit Suisse, McKinsey and many more. Feel free to check out the website link to find out more information about training offerings.

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