Master LangChain & Gen AI -BUILD #16 AI Apps HuggingFace

Master LangChain & Gen AI -BUILD #16 AI Apps HuggingFace, available at $94.99, has an average rating of 4.43, with 150 lectures, based on 1021 reviews, and has 11372 subscribers.

You will learn about Develop Langchain based AI apps Implement LLM powered apps Learn Langchain from end to end Complete project based approach This course is ideal for individuals who are Someone who ready to explore the AI world It is particularly useful for Someone who ready to explore the AI world.

Enroll now: Master LangChain & Gen AI -BUILD #16 AI Apps HuggingFace

Summary

Title: Master LangChain & Gen AI -BUILD #16 AI Apps HuggingFace

Price: $94.99

Average Rating: 4.43

Number of Lectures: 150

Number of Published Lectures: 132

Number of Curriculum Items: 150

Number of Published Curriculum Objects: 132

Original Price: ₹799

Quality Status: approved

Status: Live

What You Will Learn

Develop Langchain based AI apps
Implement LLM powered apps
Learn Langchain from end to end
Complete project based approach

Who Should Attend

Someone who ready to explore the AI world

Target Audiences

Someone who ready to explore the AI world

Are you interested in harnessing the power of AI to create groundbreaking language-based applications?

Look no further than LangChain and Gen AI – a comprehensive course that will take you from a novice to an expert in no time.

Implement Generative AI (GenAI) apps with langchain framework using different LLMs.

By implementing AI applications powered with state-of-the-art LLM models like OpenAI and Hugging Face using Python, you will embark on an exciting project-based learning journey.

With LangChain, you will gain the skills and knowledge necessary to develop innovative LLM solutions for a wide range of problems.

Here are some of the projects we will work on:

Project 1: Construct a dynamic question-answering application with the unparalleled capabilities of LangChain, OpenAI, and Hugging Face Spaces.

Project 2: Develop an engaging conversational bot using LangChain and OpenAI to deliver an interactive user experience.

Project 3: Create an AI-powered app tailored for children, facilitating the discovery of related classes of objects and fostering educational growth.

Project 4: Build a captivating marketing campaign app that utilizes the persuasive potential of well-crafted sales copy, boosting sales and brand reach.

Project 5: Develop a ChatGPT clone with an added summarization feature, delivering a versatile and invaluable chatbot experience.

Project 6: MCQ Quiz Creator App – Seamlessly create multiple-choice quizzes for your students using LangChain and Pinecone.

Project 7: CSV Data Analysis Toll – Helps you analyze your CSV file by answering your queries about its data.

Project 8: Youtube Script Writing Tool – Effortlessly create compelling YouTube scripts with this user-friendly and efficient script-writing tool.

Project 9 – Support Chat Bot For Your Website – Helps your visitors/customers to find the relevant data or blog links that can be useful to them.

Project 10 – Automatic Ticket Classification Tool – The Automatic Ticket Classification Tool categorizes support tickets based on content to streamline ticket management and response processes.

Project 11 – HR – Resume Screening Assistance – HR project using AI to assist in screening resumes, optimizing the hiring process with smart analysis and recommendations

Project 12– Email Generator using LLAMA 2- The Email Generator is a tool that automatically creates customized emails, saving time and effort in crafting personalized messages.

Project 13 – Invoice Extraction Bot using LLAMA 2- Invoice Extraction Bot: AI-powered tool that extracts key details from invoices accurately and efficiently. Simplify your data entry process.

Project 14 – Text to SQL Query Helper Tool: Convert natural language text into structured SQL queries effortlessly using the Text to SQL Query Tool for streamlined database interaction and data retrieval.

Project 15 –Customer Care Call Summary Alert – Concise notification highlighting key points and outcomes from recent customer service calls, aiding quick understanding and response

This course is designed to provide you with a complete understanding of LangChain, starting from the basics and progressing toward creating practical LLM-powered applications.

LangChain empowers programmers to fully utilize large language models, such as ChatGPT, pinecone, LLAMA 2, and Huggingface, and seamlessly integrate them with external data sources. This integration enhances the models’ ability to comprehend and respond to human language.

Built with Python, LangChain offers a user-friendly interface tailored specifically for beginners, making it accessible to aspiring developers.

Course Overview:

Aspiring to build sophisticated language-based applications

LangChain is the perfect library for you.

Move beyond basic techniques like keyword matching or rule-based systems and maximize your reach by langchain.

Leverage the power of LLMs, and applications using LangChain and combine them with cognitive or information sources & pinecone.

Unlock tremendous potential and explore new possibilities with applications using LangChain and Pinecone.

Course Contents:

LangChain

LLMs

Chat Models

Prompts

Indexes

Chains

Agents

Memory

Google Gemini Pro

But this isn’t just a theory-based course; it’s a hands-on experience. You will engage in practical activities and real-world projects, reinforcing your understanding of these concepts and techniques.

By the end of the course, you will be equipped with the skills to apply Langchain effectively, building robust, pinecone, powerful, and scalable LLM applications for various purposes.

Don’t miss this opportunity to become a language model expert.

Enroll in the LangChain course and embark on a transformative journey that will elevate your AI app development skills. LangChain , OpenAI , ChatGPT , LLM, langchain pinecone , LLAMA 2 , HuggingfaceGoogle Gemini Pro Python – these are the tools that will empower you to create cutting-edge AI applications that push the boundaries of what’s possible.

Get ready to unlock your full potential and become a hero in the world of language-based AI development through langchain.

You will do practical activities and real-world projects throughout the applications using LangChain pinecone Google Gemini Pro course to strengthen your understanding of the concepts and techniques.

You will be competent in applying Langchain pinecone to build strong, effective, and scalable LLM applications for a variety of uses by the end of the course.

Course Curriculum

Chapter 1: LangChain Introduction

Lecture 1: What You'll Get In This Course

Lecture 2: What is LangChain?

Lecture 3: ⏱️ Course RoadMap

Lecture 4: Join our online classroom

Lecture 5: A request to you… :)❤️

Lecture 6: Let's understand the LangChain and Generative AI benefits

Lecture 7: Guidelines For Source Code ✅

Chapter 2: OpenAI Introduction

Lecture 1: What is OpenAI?

Lecture 2: OpenAI API Key Generation

Chapter 3: Demo & Environment Setup

Lecture 1: A LangChain Example – Implementation Demo

Lecture 2: Anaconda Installation

Chapter 4: Langchain – Models Module Concept

Lecture 1: LangChain's Modules Overview

Chapter 5: ✅Beginner level

Lecture 1: Let's work on basic-level projects

Chapter 6: Project #1 – Simple Question & Answer App || Hugging Face Spaces || Open AI

Lecture 1: LLMs Walkthrough

Lecture 2: LLM Practical Implementation using Python

Lecture 3: LLM Practical Implementation using Python – Source Code

Lecture 4: Google Gemini Pro – Free Tier – Usage Documentation

Lecture 5: Google Gemini Pro LLM Usage Implementation – Source Code

Lecture 6: Project Environment Setup

Lecture 7: Lets' Build Simple Question Answering Application

Lecture 8: Lets' Build Simple Question Answering Application – Source Code

Chapter 7: Project #2 – Simple Conversational App || Hugging Face Spaces || OpenAI Chat

Lecture 1: Chat Model Walkthrough

Lecture 2: Chat Model Practical Implementation using Python

Lecture 3: Chat Model Practical Implementation using Python – Source Code

Lecture 4: Let's Build Simple Conversational Application

Lecture 5: Let's Build Simple Conversational Application – Source Code

Chapter 8: Project #3 – Find Similar Things App For Kids || Streamlit || Open AI Embeddings

Lecture 1: Text Embedding Walkthrough

Lecture 2: Text Embeddings Practical Implementation using Python

Lecture 3: Embeddings Practical Implementation using Python – Source Code

Lecture 4: Embeddings Example using Python

Lecture 5: Embeddings Example using Python – Source Code

Lecture 6: Let's build Similar Words Finder Application

Lecture 7: Let's build Similar Words Finder Application – Source Code

Chapter 9: Langchain – Prompt Module Concept & Implementation Using Python

Lecture 1: Prompts Module Introduction

Lecture 2: Prompt Template Walkthrough

Lecture 3: Prompt Template Walkthrough – Source Code

Lecture 4: Example Selectors Walkthrough

Lecture 5: Example Selectors Walkthrough – Source Code

Lecture 6: Adding More Examples To Input Prompt

Lecture 7: Output Parsers Walkthrough

Lecture 8: Output Parsers Walkthrough – Source Code

Chapter 10: Project #4 – Marketing Campaign App || Streamlit App || Open AI

Lecture 1: Convert Jupyter Notebook to Python Script

Lecture 2: Building the App's frontend

Lecture 3: Integration of Frontend & Backend

Lecture 4: Modularization of Code

Lecture 5: Adding Examples – Kids, Adult & Senior Citizen

Lecture 6: Marketing Campaign App – Project Source Code

Chapter 11: Langchain – Memory Module Concept

Lecture 1: Importance of Memory in LLM powered Apps

Lecture 2: Different Types of Memory

Lecture 3: Source Code

Chapter 12: Project #5 – ChatGPT Clone with Summarization Option || Streamlit App || Open AI

Lecture 1: ChatGPT Clone Demo

Lecture 2: Setting up the Project

Lecture 3: Implementing the Frontend

Lecture 4: Modularizing the Code

Lecture 5: Passing Dynamic Data

Lecture 6: Implementing Chatbot Conversational View

Lecture 7: Conversation Summarization & API key feature

Lecture 8: ChatGPT Clone with Summarization Option – Source Code

Chapter 13: Langchain – Retrieval/Data Connection Module Concept

Lecture 1: Retrieval/Data Connection Module Introduction

Lecture 2: Retrieval/Data Connection Module – Python Implementation Part 1

Lecture 3: Retrieval/Data Connection Module – Python Implementation Part 2

Lecture 4: Retrieval/Data Connection Module – Python Implementation – Source Code

Chapter 14: ✅Intermediate level

Lecture 1: Let's work on medium-level projects

Chapter 15: Project #6 – Quiz MCQ Creator App || Open AI || PINECONE || Transformers Model

Lecture 1: Loading Documents & Creating Chunks

Lecture 2: Generate Embeddings & Store Them

Lecture 3: Retrieving Answer

Lecture 4: Creating Structured Output

Lecture 5: Quiz MCQ Creator App – Source Code

Chapter 16: Langchain – Chains Module Concept

Lecture 1: Chains Overview

Lecture 2: Generic Chains

Lecture 3: Generic Chains Source Code

Lecture 4: Utility Chains

Lecture 5: Utility Chains Source Code

Chapter 17: Langchain – Agents Module Concept

Lecture 1: Agents Overview

Chapter 18: Project #7 – CSV Data Analysis Tool || OpenAI

Lecture 1: CSV Data Analysis Tool Demo

Lecture 2: CSV Data Analysis Tool – Frontend

Lecture 3: CSV Data Analysis Tool – Backend

Lecture 4: CSV Data Analysis Tool – Source Code

Chapter 19: ✅Advanced level

Lecture 1: Let's work on complex-level projects

Chapter 20: Project #8 – Youtube Script Writing Tool || OpenAI || DuckDuckGo

Lecture 1: Youtube Script Writing Tool Demo

Instructors

Sharath Raju
Senior Software Engineer – AI & Robotics

Rating Distribution

1 stars: 13 votes
2 stars: 18 votes
3 stars: 72 votes
4 stars: 310 votes
5 stars: 608 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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