AI Apps with ChatGPT and LangChain: The Introduction
AI Apps with ChatGPT and LangChain: The Introduction, available at $89.99, has an average rating of 4.45, with 43 lectures, based on 22 reviews, and has 271 subscribers.
You will learn about Understand Large Language Models and how to use them in AI Apps, how to prepare inputs, call GPT API endpoints and process outputs. Core Prompting Techniques: Instructions, Zero-Shot, Few-Shot, Self Confidence, Chain-of-Thoughts, Output Formatting to JSON Strings, etc. Using ChatGPT API in Natural Language Processing tasks: Named Entity Extraction, Classification, Sentiment Analysis, Translation. Manage chat history with LangChain Conversation Memory classes, including Window Buffer, Token Buffer and Summary, enabling sophisticated, intelligent chatbots. Use Embeddings to create Vector Databases and Semantic Similarity Search to retrieve relevant documents to chat with PDF or HTML docs and Source Code. Summarise long texts with LangChain Map-Reduce and Refine Chains, including PDFs, web pages, YouTube video transcripts. Use ReAct and OpenAI Functions Agent Classes to develop reasoning Agents capable of dealing with complex problems, requiring sequence of steps to solve. Build Chat applications to perform ad hoc Data Analysis with Pandas dataframes or SQL databases. Develop intuitions about how all these work and can be applied to solve real tasks. Learn latest and greatest Python libraries to build LLM enabled applications, including the famous LangChain. This course is ideal for individuals who are Developers wishing to kick off their career into orbit by learning bleeding edge skills of creating Generative AI applications or Python programmers curious about inner workings of ChatGPT and Plugins or System Architects investigating applicabilities of Generative AI and LLMs in Business Applications It is particularly useful for Developers wishing to kick off their career into orbit by learning bleeding edge skills of creating Generative AI applications or Python programmers curious about inner workings of ChatGPT and Plugins or System Architects investigating applicabilities of Generative AI and LLMs in Business Applications.
Enroll now: AI Apps with ChatGPT and LangChain: The Introduction
Summary
Title: AI Apps with ChatGPT and LangChain: The Introduction
Price: $89.99
Average Rating: 4.45
Number of Lectures: 43
Number of Published Lectures: 43
Number of Curriculum Items: 43
Number of Published Curriculum Objects: 43
Original Price: $24.99
Quality Status: approved
Status: Live
What You Will Learn
- Understand Large Language Models and how to use them in AI Apps, how to prepare inputs, call GPT API endpoints and process outputs.
- Core Prompting Techniques: Instructions, Zero-Shot, Few-Shot, Self Confidence, Chain-of-Thoughts, Output Formatting to JSON Strings, etc.
- Using ChatGPT API in Natural Language Processing tasks: Named Entity Extraction, Classification, Sentiment Analysis, Translation.
- Manage chat history with LangChain Conversation Memory classes, including Window Buffer, Token Buffer and Summary, enabling sophisticated, intelligent chatbots.
- Use Embeddings to create Vector Databases and Semantic Similarity Search to retrieve relevant documents to chat with PDF or HTML docs and Source Code.
- Summarise long texts with LangChain Map-Reduce and Refine Chains, including PDFs, web pages, YouTube video transcripts.
- Use ReAct and OpenAI Functions Agent Classes to develop reasoning Agents capable of dealing with complex problems, requiring sequence of steps to solve.
- Build Chat applications to perform ad hoc Data Analysis with Pandas dataframes or SQL databases.
- Develop intuitions about how all these work and can be applied to solve real tasks.
- Learn latest and greatest Python libraries to build LLM enabled applications, including the famous LangChain.
Who Should Attend
- Developers wishing to kick off their career into orbit by learning bleeding edge skills of creating Generative AI applications
- Python programmers curious about inner workings of ChatGPT and Plugins
- System Architects investigating applicabilities of Generative AI and LLMs in Business Applications
Target Audiences
- Developers wishing to kick off their career into orbit by learning bleeding edge skills of creating Generative AI applications
- Python programmers curious about inner workings of ChatGPT and Plugins
- System Architects investigating applicabilities of Generative AI and LLMs in Business Applications
ChatGPT revolutionises businesses, how we work and greatly influences our lives. It is much more than a famous Web and mobile applications everyone is using now. Its creators recently released a publicly available API enabling creation of sophisticated AI Apps utilising the power of GPT models to most difficult Natural Language Processing tasks and beyond.
This course aims at Python developers to teach how to harness the power of latest and greatest Large Language Models in custom, innovative applications, how to interface existing data in various formats with ChatGPT available through the API.
You will learn the magic of LangChain – the Python Library delivering ever growing ecosystem of tools and integrations necessary to build the AI Apps. LangChain offers not only convenient wrappers around ChatGPT model APIs, but has plenty of ready-made classes and functions facilitating creation and use of Chat Memory, Vector DBs for semantic search of relevant documents, and blueprints of powerful Agents, capable of using Python functions in your environment to get access to local, proprietary data.
The course is very practical and consists of dozens of practical demonstrations of Python code solving various AI tasks. You will get detailed, precise and in-depth explanation of all presented concepts and algorithms.
All of the code used in the course is available for your download from GitHub repository. You can use it as a basis to further exploration and experimentation leading to quick and easy development of real-life AI Apps.
Course Curriculum
Chapter 1: Course Introduction
Lecture 1: Introduction
Lecture 2: Downloading course materials and setting up the environment
Chapter 2: Introduction to LLMs
Lecture 1: Large Language Models
Lecture 2: ChatGPT – a prime example of LLM
Lecture 3: ChatGPT for Developers
Lecture 4: Examples of tasks solved with ChatGPT
Chapter 3: Getting started with OpenAI API and LangChain
Lecture 1: Model variants in OpenAI API
Lecture 2: Setting up an OpenAI API account
Lecture 3: Using LangChain library to interact with OpenAI API
Lecture 4: In-Context Learning and Action Planning design patterns
Lecture 5: Overview of LangChain concepts
Chapter 4: Prompt Engineering for Developers
Lecture 1: Basic prompt tactics
Lecture 2: Prompt techniques to improve output quality
Lecture 3: Prompt Templates
Lecture 4: Post-processing of ChatGPT responses
Lecture 5: Introduction to Chains
Lecture 6: Moderation techniques
Lecture 7: Example AI App: Analysis of Customer Reviews
Chapter 5: Chatbots
Lecture 1: Closer look at Chat vs QA
Lecture 2: Chat conversation memory
Lecture 3: Interactive Chatbot in Jupyter notebook
Lecture 4: Handling long chat memory
Chapter 6: Documents and Web pages
Lecture 1: Summary of long PDF document
Lecture 2: Summary with Refine chain
Lecture 3: Working with Web pages
Lecture 4: Summarising YouTube video transcript
Lecture 5: Naive QA with a PDF document
Chapter 7: Vector Databases
Lecture 1: Semantic search and Text embeddings
Lecture 2: QA over a PDF document with Vector DB
Lecture 3: QA with Pandas User Guide – Build Persistent Vector Database
Lecture 4: QA with Pandas User Guide – Use Persistent Vector Database
Lecture 5: QA with TikToken code
Lecture 6: QA with Vector DB – Limitations
Chapter 8: Action planning agents
Lecture 1: Smooth intro to Agents
Lecture 2: ReAct Agent internals
Lecture 3: OpenAI Functions agent
Lecture 4: OpenAI Functions agent with chat memory
Lecture 5: Agent with Vector DB
Lecture 6: Web search with Bing
Lecture 7: Action planning and custom tools
Lecture 8: CSV file with Pandas agent
Lecture 9: SQL Database agent
Lecture 10: Managing multiple Tools
Instructors
-
Kris Celmer
Seasoned IT Infrastructure Professional – Cloud Expert
Rating Distribution
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- 2 stars: 0 votes
- 3 stars: 1 votes
- 4 stars: 7 votes
- 5 stars: 14 votes
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