Packt
LangChain MasterClass: Build 15 LLM Apps with Python
Packt

LangChain MasterClass: Build 15 LLM Apps with Python

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

13 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

13 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Design automated marketing and customer support tools.

  • Analyze and streamline data analysis and CSV processing.

  • Develop skills in invoice data extraction and SQL query tools.

Details to know

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Recently updated!

September 2024

Assessments

10 assignments

Taught in English

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There are 25 modules in this course

In this module, we will introduce you to LangChain, an open-source framework designed to facilitate the creation of applications powered by large language models. We will discuss the objectives and benefits of LangChain and provide an overview of what you will gain from this course.

What's included

3 videos1 reading

In this module, we will delve into the foundational aspects of OpenAI, exploring its history and powerful language models like GPT-3 and Codex. Additionally, we will cover the practical steps to set up and utilize OpenAI's API for various applications.

What's included

2 videos

In this module, we will demonstrate a practical implementation of LangChain to improve question-answering capabilities and guide you through the installation of Anaconda, which is essential for our upcoming projects using Jupyter Notebooks.

What's included

2 videos1 assignment

In this module, we will provide an overview of the different modules within LangChain, including models, prompts, memory, indexes, chains, agents, and callbacks, highlighting their functionalities and practical applications.

What's included

1 video

In this module, we will walk you through the creation of a simple question-answering app using LangChain. You will explore different models, set up the project environment, and build an application that utilizes LangChain for effective AI-driven interactions.

What's included

4 videos

In this module, we will guide you through the development of a simple conversational app using LangChain. You will learn to configure the environment, set up the chatbot, and implement custom conversational contexts for an interactive user experience.

What's included

3 videos1 assignment

In this module, we will explore word embeddings and their applications in machine learning projects. You will learn to implement text embeddings using LangChain and build an application that helps children understand similar words and objects.

What's included

4 videos

In this module, we will delve into the prompts module in LangChain, learning how to design effective prompts, use prompt templates, and explore features like example selectors and output parsers to optimize the model's responses.

What's included

5 videos

In this module, we will build a marketing campaign app using LangChain. You will learn to convert Jupyter Notebooks to Python scripts, develop a user interface with Streamlit, and integrate frontend and backend components for a seamless application.

What's included

5 videos1 assignment

In this module, we will focus on the memory modules in LangChain, highlighting the importance of conversation buffer memory and exploring different types of memory to enhance AI interactions by retaining and recalling past conversations.

What's included

2 videos

In this module, we will guide you through the creation of a ChatGPT clone with summarization capabilities. You will learn to set up the project environment, implement a conversational view, and enhance the chatbot with features like dynamic inputs and user API keys.

What's included

7 videos

In this module, we will delve into the Data Connection module in LangChain, exploring its importance and functionality. You will learn to process data, create vector embeddings, and use retrievers to fetch relevant information efficiently.

What's included

3 videos1 assignment

In this module, we will build an MCQ creator app using LangChain. You will learn to load documents, create embeddings, retrieve answers, and format the output in an MCQ format for practical applications.

What's included

4 videos

In this module, we will explore the concept of chains within LangChain, learning how to connect different LLMs, implement generic and sequential chains, and utilize utility chains for simplifying complex tasks and saving development time.

What's included

3 videos

In this module, we will explore the concepts of action agents and plan and execute agents within LangChain. You will learn how these agents make decisions and create plans, combining their functionalities for smarter and more efficient outcomes.

What's included

1 video1 assignment

In this module, we will create a data analysis tool that processes CSV files based on user queries. You will learn to set up the application, implement the UI, and use LangChain and OpenAI to analyze and generate responses from CSV data.

What's included

3 videos

In this module, we will develop a YouTube script-writing tool using LangChain. You will learn to set up the project environment, create the UI, and integrate LangChain to generate dynamic and engaging video scripts based on user inputs.

What's included

4 videos

In this module, we will guide you through the creation of a support chatbot for websites using LangChain. You will learn to implement data scraping, set up a user interface, and integrate frontend and backend components to provide natural language assistance on your website.

What's included

6 videos1 assignment

In this module, we will build an automatic ticket classification tool using LangChain. You will learn to implement the UI, handle document uploads, and train a classification model to categorize tickets into different departments based on user queries.

What's included

8 videos

In this module, we will create a resume screening assistance tool for HR using LangChain. You will learn to set up the project, analyze resumes, and match them with job descriptions, simplifying the screening process and enhancing HR efficiency.

What's included

5 videos

In this module, we will introduce you to the LLAMA 2 model, a powerful open-source tool offered by Meta. You will learn about its versions, parameter sizes, and potential applications in generative AI, along with the steps to download and set up LLAMA 2 for local use.

What's included

1 video1 assignment

In this module, we will guide you through the development of an email generator using LangChain and LLAMA 2. You will learn to set up the project, design the UI, and implement the LLAMA 2 model to generate dynamic and personalized email content.

What's included

2 videos

In this module, we will build an invoice extraction bot using LangChain and LLAMA 2. You will learn to implement data extraction from PDF invoices, process the extracted data, and create a user interface for viewing and downloading the results.

What's included

6 videos1 assignment

In this module, we will create a text-to-SQL query helper tool using LangChain, Google Colab, and LLAMA 2. You will learn to set up the environment, implement pipelines for text prediction, and utilize LangChain to generate SQL queries based on user inputs.

What's included

2 videos

In this module, we will build a customer care call summary alert tool using LangChain, OpenAI, and Zapier. You will learn to implement the UI and backend logic for processing call data, automate the summarization, and set up an email alert system for efficient customer care management.

What's included

4 videos2 assignments

Instructor

Packt - Course Instructors
Packt
371 Courses9,410 learners

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