Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
1 Hour(s) 48 Minute(s)
Language
English
Taught by
Jit Sinha
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
Course Overview
Unlocking the Power of LLMs with LangChain
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 – making AI application development truly easy!
Course Content
- 10 section(s)
- 46 lecture(s)
- Section 1 Introduction to LangChain
- Section 2 Models
- Section 3 Prompts
- Section 4 Chains
- Section 5 Memory
- Section 6 Index
- Section 7 Agents
- Section 8 Streamlit
- Section 9 Project 1: Question Answering Over Documents
- Section 10 Project 2: Interactive chatbot with Streamlit and OpenAI
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
Skills covered in this course
Reviews
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JJitesh Saha
this course is very useful for people looking to understand and apply LangChain in their AI projects. Although it assumes some prior knowledge in Python, the content and practical application in code makes it a worth watching
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SShyamalie Shubhra
The course gives a thorough introduction to LangChain, covers in depth knowledge on topics that were particularly interesting to me like prompt and memory management. A must watch for AI enthusiasts!
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AAhmed Atallah Alenazi
the course was good in information's and explaining but it didn't explain how the python code worked
