AI Applications Made Easy: Dive into LangChain & GPT

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Jit Sinha

1:48:16

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1. Introduction to LangChain

1. LangChain Demo.mp4

02:13

2. Introduction.mp4

02:03

3. What is Langchain.mp4

02:25

4. Why use LangChain.mp4

00:22

5. Real Life Examples.mp4

01:24

6. Components of LangChain.mp4

03:54

7. Installation and setup.mp4

02:10

2. Models

1. Introduction.mp4

00:24

2. Large Language Models.mp4

02:20

3.1 working with large language models.zip

3. Working with Large Language models.mp4

02:44

4. Chat Models.mp4

01:28

5.1 working with chat models.zip

5. Working with Chat Models.mp4

01:49

3. Prompts

1. Prompt Templates.mp4

01:37

2.1 working with prompt template.zip

2. Working with Prompt Templates.mp4

00:59

3. Example Selectors.mp4

01:29

4.1 working with example selectors.zip

4. Working with Example Selectors.mp4

00:57

5. Few Shot Prompt Templates.mp4

01:19

6.1 working with few-shot prompt templates with example set.zip

6. Working with Few Shot Prompt Templates - using Example Sets.mp4

06:26

7.1 working with few-shot prompt templates using example selectors.zip

7. Working with Few Shot Prompt Templates - using Example Selectors.mp4

03:35

8. Output Parsers.mp4

03:43

9.1 implementing pydanticoutputparser.zip

9. Working with Output Parsers.mp4

02:44

4. Chains

1. Introduction.mp4

00:31

2. LLM Chains.mp4

00:16

3.1 working with llmchain.zip

3. Working with LLM Chains.mp4

01:19

4. Sequential Chain.mp4

00:26

5.1 simple sequential chain.zip

5. Working with Sequential Chain.mp4

03:08

5. Memory

1. Introduction.mp4

00:33

2. How does memory work in LangChain.mp4

01:22

3.1 working with memory.zip

3. Working with Memory.mp4

03:48

4.1 memory with chains.zip

4. How to use Memory in Chain.mp4

03:40

6. Index

1. Introduction.mp4

03:23

2. Document Loaders.mp4

01:01

3.1 working with document loaders.zip

3. Working with Document Loaders.mp4

01:30

4. Text Splitters.mp4

01:08

5.1 working with text splitters.zip

5. Working with Text Splitters.mp4

01:31

6. Embedding.mp4

02:35

7. Vector Stores.mp4

02:02

8.1 working with vectorstore.zip

8. Working with Vector Stores.mp4

01:44

7. Agents

1. Introduction.mp4

03:21

2.1 working with agents.zip

2. Working with Agents.mp4

04:54

8. Streamlit

1. Introduction.mp4

03:29

2. Working with Streamlit.mp4

04:18

9. Project 1 Question Answering Over Documents

1. Introduction.mp4

02:01

2.1 question answering over documents - jupyter.zip

2. Code Walkthrough - Jupyter.mp4

05:38

10. Project 2 Interactive chatbot with Streamlit and OpenAI

1. Chatbot Demonstration.mp4

04:09

2. Code Walkthrough.mp4

04:24

Description

Unlocking the Power of LLMs with LangChain

What You'll Learn?

Master Industry-Standard Tools and Frameworks: Learn the ins and outs of LangChain and get up to speed with Large Language Models (LLMs) from industry leaders
Unlock the Power of Prompts: Acquire the skills to create, call, and chain prompts effectively, enabling you to develop interactive and dynamic applications tha
Real-World Application: Apply what you've learned by using LLM techniques on personal documents and projects. This practical experience will arm you with the kn
Delve into Advanced Chatbot Development: Develop an in-depth understanding of how to build conversational chatbots using LangChain. Learn to utilize memory func
LangChain Components: Chains, Agents, DocumentLoader, TextSplitter, OutputParser, Memory
Vector Storage/Vector Databases (Pinecone, Chroma)
Basics of Streamlit which is an open-source Python library that makes it easy to create and share beautiful, custom web apps for AI

Who is this for?

Engineers across various domains—software, backend, and full-stack—are interested in learning how to develop Generative AI applications using LangChain.

What You Need to Know?

Basic understanding of LLMs and programming experience with Python!

More details

Description
AI Applications Made Easy: Dive into LangChain & GPT
Welcome to a transformative learning journey designed to demystify the art of building powerful AI applications using the LangChain framework and the groundbreaking GPT models by OpenAI.
Course Overview:
In this comprehensive course, participants will:
Embark on an AI Odyssey: Begin with an insightful introduction to LangChain, uncovering its potential and importance in the realm of advanced AI solutions. Understand why LangChain stands out in the vast AI landscape and how it's shaping the future.
Deconstruct the DNA of LangChain: Dive deep into the intricate components of LangChain. From the core models that drive its intelligence to the agents that act as its emissaries, understand the mechanisms of prompts, chains, indexes, and the dynamic memory system that allows for seamless learning and recall.
Expand Horizons with External Tools: Integrate LangChain's prowess with the web framework Streamlit. This module offers a hands-on approach to building interactive web interfaces and showcases how LangChain can harmoniously blend with other software tools, multiplying its capabilities.
Witness AI in Action: Transition from theory to practice by exploring live examples. Witness the end-to-end process of ideating, designing, and executing real-world applications. Additionally, students will be encouraged to lead projects, fostering a space for innovation and collaborative brainstorming.
By the end of this course, participants will not only possess a robust understanding of LangChain and GPT but also acquire the skills and confidence to design, develop, and deploy impressive AI applications tailored to diverse needs.
Whether you're an AI enthusiast, a budding developer, or a seasoned professional looking to enhance your toolkit, this course promises a blend of theory, practice, and innovation â€“ making AI application development truly easy!
Who this course is for:
Engineers across various domainsâ€”software, backend, and full-stackâ€”are interested in learning how to develop Generative AI applications using LangChain.

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Artificial Intelligence

Jit Sinha

Instructor's Courses

Having over 12 years of deep-rooted industry experience, he has built an esteemed career as a Solutions Architect, skillfully crafting and executing intricate solutions that fuel efficiency and innovation.Jit holds a trio of prestigious cloud certifications: AWS Certified Solutions Architect - ProfessionalMicrosoft Certified: Azure Solutions Architect Expert Google Cloud Certified: Professional Cloud ArchitectThese qualifications reflect Jit's comprehensive knowledge across various cloud platforms, enabling a unique capacity to strategize and operate optimally in diverse cloud environments and, consequently, deliver integrative and expansive solutions.In addition to his remarkable achievements in cloud architecture, he is also a certified Architect in Splunk. This further emphasizes his capacity to lead in data-intensive environments, leveraging the potential of real-time operational intelligence to inform decision-making and shape strategic direction.Throughout his illustrious career, he has consistently demonstrated an ability to decode complex technical scenarios into straightforward, implementable solutions that yield results. His broad knowledge, coupled with a steadfast commitment to excellence, firmly establishes him as a true industry leader in the realm of solution architecture.

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