LangChain MasterClass- OpenAI LLAMA 2 LLM AI Apps|| Gen AI
Discover real-world uses of LangChain, Pinecone, OpenAI, LLAMA 2 ,LLM Build AI Apps Generative AI - Hugging Face
Lo que serás capaz de hacer
Unlock the Power of AI with LangChain: Learn to Create Revolutionary Language-Based Applications Looking to harness the full potential of AI and revolutionize the world of language-based applications? Look no further than LangChain, the comprehensive course designed to transform you from a novice to an expert in record time . Gen AI apps and LLM projects! Dive into hands-on projects that will shape your expertise, including: Project 1: Construct a dynamic question-answering application with the unparalleled capabilities of LangChain, OpenAI, and Hugging Face Spaces, Google Gemini Pro . 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. Course Content: In this course, we will explore the capabilities of LangChain, an open-source framework that combines LLMs like GPT-4 with external computation and data sources to build scalable and performant AI applications. You will gain in-depth knowledge of LangChain components, including LLM wrappers, Chains, and Agents. Additionally, we will delve into embeddings and vector databases, with a focus on Pinecone. Through a learning-by-doing approach, we will collaboratively build real-world LLM applications using Python, LangChain, and OpenAI, complete with modern web app front-ends developed with Streamlit. Course Highlights: Unlock the true potential of LangChain, LLMs, Google Gemini Pro , Chat Models, Prompts, Indexes, Data Connections, Chains, Agents, and Memory. Harness the power of LLMs and LangChain to develop robust applications, integrating cognitive and information sources with Pinecone. Explore new horizons and unleash unprecedented possibilities with LangChain and Google Gemini Pro , Pinecone-powered applications.
- Helps you to create LLM powered applications usimg Langchain that will help you save time and increase efficiency
- By the end of the course , you will be capable of working on langchain LLM real time projects
- Explore useful concepts that can be used in your Langchain projects
- You will gain a solid understanding of LangChain components like LLM wrappers, prompt templates, and Memory.
- Additionally, we will delve into the concept of embeddings and vector data stores, learning how to utilize them effectively to enhance the performance of LangCh
- Project 1: Construct a question-answering application powered by LLM using LangChain, OpenAI, and Hugging Face Spaces.
Temario
UNIDAD 1 - LangChain Introduction · 7 leccionesUNIDAD 1 - LangChain Introduction
UNIDAD 1 - LangChain Introduction
- What You'll Get In This Course
- Generative AI Introduction
- What is LangChain?
- ⏱️ Course RoadMap
- A request to you... :)❤️
- Let's understand the LangChain benefits
- Guidelines For Source Code ✅
UNIDAD 2 - HuggingFace Introduction · 1 leccionesUNIDAD 2 - HuggingFace Introduction
UNIDAD 2 - HuggingFace Introduction
- HuggingFace Intro & Access Token Generation
UNIDAD 3 - OpenAI Introduction · 2 leccionesUNIDAD 3 - OpenAI Introduction
UNIDAD 3 - OpenAI Introduction
- What is OpenAI?
- OpenAI API Key Generation
UNIDAD 4 - Demo & Environment Setup · 2 leccionesUNIDAD 4 - Demo & Environment Setup
UNIDAD 4 - Demo & Environment Setup
- A LangChain Example - Implementation Demo
- Anaconda Installation
UNIDAD 5 - Langchain - Models Module Concept · 1 leccionesUNIDAD 5 - Langchain - Models Module Concept
UNIDAD 5 - Langchain - Models Module Concept
- LangChain's Modules Overview
UNIDAD 6 - ✅***Beginner level*** · 1 leccionesUNIDAD 6 - ✅***Beginner level***
UNIDAD 6 - ✅***Beginner level***
- Let's work on basic-level projects
UNIDAD 7 - Project #1 - Simple Question & Answer App · 4 leccionesUNIDAD 7 - Project #1 - Simple Question & Answer App
UNIDAD 7 - Project #1 - Simple Question & Answer App
- LLMs Walkthrough & HuggingFace Token Generation
- LLM Practical Implementation using Python
- Project Environment Setup
- Lets' Build Simple Question Answering Application
UNIDAD 8 - Project #2 - Simple Conversational App · 3 leccionesUNIDAD 8 - Project #2 - Simple Conversational App
UNIDAD 8 - Project #2 - Simple Conversational App
- Chat Model Walkthrough
- Chat Model Practical Implementation using Python
- Let's Build Simple Conversational Application
UNIDAD 9 - Project #3 - Find Similar Things App For Kids · 3 leccionesUNIDAD 9 - Project #3 - Find Similar Things App For Kids
UNIDAD 9 - Project #3 - Find Similar Things App For Kids
- Text Embedding Walkthrough
- Text Embeddings Practical Implementation using Python
- Let's build Similar Words Finder Application
UNIDAD 10 - Langchain - Prompt Module Concept & Implementation Using Python · 5 leccionesUNIDAD 10 - Langchain - Prompt Module Concept & Implementation Using Python
UNIDAD 10 - Langchain - Prompt Module Concept & Implementation Using Python
- Prompts Module Introduction
- Prompt Template Walkthrough
- Example Selectors Walkthrough
- Adding More Examples To Input Prompt
- Output Parsers Walkthrough
UNIDAD 11 - Project #4 - Marketing Campaign App · 6 leccionesUNIDAD 11 - Project #4 - Marketing Campaign App
UNIDAD 11 - Project #4 - Marketing Campaign App
- Convert Jupyter Notebook to Python Script
- Building the App's frontend
- Integration of Frontend & Backend
- Modularization of Code
- Adding Examples - Kids, Adult & Senior Citizen
- Project Source Code
UNIDAD 12 - Langchain - Memory Module Concept · 3 leccionesUNIDAD 12 - Langchain - Memory Module Concept
UNIDAD 12 - Langchain - Memory Module Concept
- Importance of Memory in LLM powered Apps
- Different Types of Memory
- Source Code
UNIDAD 13 - Project #5 - ChatGPT Clone with Summarization Option · 8 leccionesUNIDAD 13 - Project #5 - ChatGPT Clone with Summarization Option
UNIDAD 13 - Project #5 - ChatGPT Clone with Summarization Option
- ChatGPT Clone Demo
- Setting up the Project
- Implementing the Frontend
- Modularizing the Code
- Passing Dynamic Data
- Implementing Chatbot Conversational View
- Conversation Summarization & API key feature
- Source Code
UNIDAD 14 - Langchain - Data Connection Module Concept · 4 leccionesUNIDAD 14 - Langchain - Data Connection Module Concept
UNIDAD 14 - Langchain - Data Connection Module Concept
- Data Connnection Module Introduction
- Data Connection Module - Python Implementation Part 1
- Data Connection Module - Python Implementation Part 2
- Source Code
UNIDAD 15 - ✅***Intermediate level*** · 1 leccionesUNIDAD 15 - ✅***Intermediate level***
UNIDAD 15 - ✅***Intermediate level***
- Let's work on medium-level projects
UNIDAD 16 - Project #6 - Quiz MCQ Creator App · 5 leccionesUNIDAD 16 - Project #6 - Quiz MCQ Creator App
UNIDAD 16 - Project #6 - Quiz MCQ Creator App
- Loading Documents & Creating Chunks
- Generate Embeddings & Store Them
- Retrieving Answer
- Creating Structured Output
- Source Code
UNIDAD 17 - Langchain - Chains Module Concept · 3 leccionesUNIDAD 17 - Langchain - Chains Module Concept
UNIDAD 17 - Langchain - Chains Module Concept
- Chains Overview
- Generic Chains
- Utility Chains
UNIDAD 18 - Langchain - Agents Module Concept · 1 leccionesUNIDAD 18 - Langchain - Agents Module Concept
UNIDAD 18 - Langchain - Agents Module Concept
- Agents Overview
UNIDAD 19 - Project #7 - CSV Data Analysis Tool · 4 leccionesUNIDAD 19 - Project #7 - CSV Data Analysis Tool
UNIDAD 19 - Project #7 - CSV Data Analysis Tool
- CSV Data Analysis Tool Demo
- CSV Data Analysis Tool - Frontend
- CSV Data Analysis Tool - Backend
- CSV Data Analysis Tool - Source Tool
UNIDAD 20 - ✅***Advanced level*** · 1 leccionesUNIDAD 20 - ✅***Advanced level***
UNIDAD 20 - ✅***Advanced level***
- Let's work on complex-level projects
UNIDAD 21 - Project #8 - Youtube Script Writing Tool · 5 leccionesUNIDAD 21 - Project #8 - Youtube Script Writing Tool
UNIDAD 21 - Project #8 - Youtube Script Writing Tool
- Youtube Script Writing Tool Demo
- Youtube Script Writing tool - Frontend
- Youtube Script Writing tool - Backend
- Youtube Script Writing tool - Integration
- Youtube Script Writing Tool - Source Code
UNIDAD 22 - Project #9 - Support Chat Bot For Your Website · 8 leccionesUNIDAD 22 - Project #9 - Support Chat Bot For Your Website
UNIDAD 22 - Project #9 - Support Chat Bot For Your Website
- Support Chat Bot For Your Website Demo
- Flow Diagram
- Implement Frontend for Pushing Data to Pinecone
- Implementing Backend for Scraping the Data
- Implementing Backend for Pushing the Data to Pinecone
- Handling the Hardcoded Values
- Implementing Information Retrieval System
- Support Chat Bot For Your Website - Source Code
UNIDAD 23 - Project #10 - Automatic Ticket Classification Tool · 9 leccionesUNIDAD 23 - Project #10 - Automatic Ticket Classification Tool
UNIDAD 23 - Project #10 - Automatic Ticket Classification Tool
- Automatic Ticket Classification Tool - Demo
- Upload Documents To Pinecone - Frontend & Backend
- Chatbot Interaction- Frontend & Backend
- Organizing Different Pages in Streamlit
- Classification Model Creation
- Model Training Process
- Ticket Raising Feature Implementation
- Viewing Pending Tickets Tab
- Source Code
UNIDAD 24 - Project #11 - HR - Resume Screening Assistance · 6 leccionesUNIDAD 24 - Project #11 - HR - Resume Screening Assistance
UNIDAD 24 - Project #11 - HR - Resume Screening Assistance
- HR - Resume Screening Assistance - Demo
- Resume Screening Assistance Frontend
- Loading Documents and Adding Metadata
- Push & Pull Data From Pinecone
- Finetuning Output
- HR - Resume Screening Assistance - Source Code
UNIDAD 25 - LLAMA 2 Introduction · 1 leccionesUNIDAD 25 - LLAMA 2 Introduction
UNIDAD 25 - LLAMA 2 Introduction
- LLAMA 2 Introduction
UNIDAD 26 - Project #12 - Email Generator Using LLAMA 2 || Streamlit App · 3 leccionesUNIDAD 26 - Project #12 - Email Generator Using LLAMA 2 || Streamlit App
UNIDAD 26 - Project #12 - Email Generator Using LLAMA 2 || Streamlit App
- Email Generator Front End & Module Creation
- Using LLAMA 2 as LLM & Execution
- Email Generator App - Source Code
UNIDAD 27 - Project #13 - Invoice Extraction Bot · 7 leccionesUNIDAD 27 - Project #13 - Invoice Extraction Bot
UNIDAD 27 - Project #13 - Invoice Extraction Bot
- Invoice Extraction Bot - StreamLit Frontend
- Replicate Platform Introduction
- Get Replicate API Token
- Data Extraction
- LLAMA 2 - LLM setup
- Formating Output & Download Option
- Project 13 - Invoice Extraction Bot - Source Code
UNIDAD 28 - Project #14 - Text to SQL Query - Helper Tool || Google Collab || LLAMA 2 · 3 leccionesUNIDAD 28 - Project #14 - Text to SQL Query - Helper Tool || Google Collab || LLAMA 2
UNIDAD 28 - Project #14 - Text to SQL Query - Helper Tool || Google Collab || LLAMA 2
- Project Setup & Huggingface Login
- Pipeline Creation & Prediction
- Source Code
UNIDAD 29 - Project #15 - Customer Care Call Summary Alert || OpenAI || Zapier NLA · 5 leccionesUNIDAD 29 - Project #15 - Customer Care Call Summary Alert || OpenAI || Zapier NLA
UNIDAD 29 - Project #15 - Customer Care Call Summary Alert || OpenAI || Zapier NLA
- Customer Care Call Summary Alert - Demo
- 1. Frontend Implemention
- 2. Backend Implemention
- 3. Final Execution
- Source Code
Tu certificado lo emite la SEP, no solo una plataforma
Al demostrar la competencia recibes un certificado emitido por la Secretaría de Educación Pública a través del Gobierno del Estado de México: un documento oficial que puedes presentar con confianza ante cualquier empleador o institución.
Tu certificado con INEC
- Lo emite la Secretaría de Educación Pública (SEP), a través del Gobierno del Estado de México
- Documento oficial con folio verificable en línea
- Lo otorga la Universidad Tecnológica Fidel Velázquez
Otras plataformas en línea
- Constancia privada emitida por la misma plataforma
- Solo acredita horas cursadas o asistencia
- Sin respaldo de una autoridad educativa
Tu itinerario, de la inscripción al certificado
- 1
Inscripción con pago único
Pagas $2,800 MXN una sola vez y entras de inmediato al curso.
- 2
Estudias a tu ritmo
29 unidades con videos, lecturas y actividades, disponibles 24/7 durante 12 meses.
- 3
Cuestionarios por unidad
Cuestionarios para comprobar lo aprendido.
- 4
Certificado
Emitido por la SEP a través del Gobierno del Estado de México, con folio verificable.
Un certificado oficial de la SEP
- Emitido por la Secretaría de Educación Pública (SEP), a través del Gobierno del Estado de México. No es una constancia privada: es un documento oficial, y ese respaldo marca la diferencia frente a otras plataformas en línea.
- Contenido impartido por Sharath Raju.
- Folio y QR verificables para compartirlo con quien te contrate.
Empieza hoy, a tu ritmo
Un solo pago y acceso inmediato al curso completo durante 12 meses.
- 29 unidades · 112 lecciones · 60 h
- 12 meses de acceso
- Certificado emitido por la SEP (Gob. del Estado de México) con folio verificable
Sobre tu inscripción
¿Cómo es el pago?
Un solo pago de $2,800 MXN. No hay mensualidades ni cargos recurrentes.
¿Cuánto tiempo tengo acceso?
12 meses desde tu inscripción, 24/7, para avanzar a tu ritmo.
¿Quién imparte el contenido?
El curso es impartido por Sharath Raju; INEC gestiona tu inscripción, evaluación y certificado.
¿Qué pasa cuando vence mi acceso?
Puedes renovar tu cuenta tú mismo desde la plataforma, sin trámites ni esperas.


