Build and Launch Your First Generative AI App

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About the Course

4 Hours of On-Demand Course Videos

Get lifetime access to all course modules, updates, and course notes.

2 Full-Stack Projects

What’s the point of a credential if you don’t walk away with real-world project?

Community of Like-minded Learners

Engage with a thriving community of like-minded learners on Discord.

M-F Full Support from the Course Instructor

Weekday support with a dedicated private Discord community for networking and problem-solving.

Learning Outcomes

Fontend

  • Use a prebuilt NextJS template to build a beautiful chatbot user experience
  • Pre-styled with Tailwind
  • Host your generative AI app with Vercel

Backend

  • Hassle-free deployment to the cloud with AWS microservices
  • Store chat messages in a low latency AWS DynamoDB table

Generative AI

  • VOICE: Bring your app to life with the ElevenLabs API, accessing thousands of voices.
  • TEXT: Use the latest OpenAI GPT models like GPT-3.5-Turbo, GPT-4, and GPT-4o to build powerful models
  • FUNCTIONS: Leverage OpenAI Function Calling to give GPT control of your codebase

Vector Databases

  • RAG: Learn how to make a data driven AI application using OpenAI Embeddings
  • VECTOR STORES: Use the most popular vector database, Pinecone to store and access your search queries.
  • INTEGRATIONS: Add any data source from PDFs, websites, to videos, or custom internal data.

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Course Projects

Full-Stack Projects in this Course

Project 1

KitsuneAI

KitsuneAI is a unique, personalized chatbot project that integrates cutting-edge technologies to create an engaging and interactive experience. This project combines a NextJS frontend, an AWS Chalice backend, and various AWS services to create a chatbot that can respond to user messages and convert text responses into audio.

What You'll Build:

  • Interactive Chatbot: Create a chatbot that can hold conversations and adapt its responses based on the user’s inputs.
  • Voice Integration: Learn to convert text responses into audio, making interactions more lifelike.
  • Customizable Characters: Tailor the chatbot’s personality and responses to act as a girlfriend, therapist, or personal trainer.
  • Data Persistence: Store chat history using AWS DynamoDB, ensuring seamless user experiences even after refreshing or closing the page.

Key Technologies You'll Learn:

  • Frontend with NextJS: Build a user-friendly interface for your chatbot.
  • Backend with AWS Chalice: Develop a robust backend using AWS Chalice, a serverless framework for creating Python APIs.
  • AWS Services: Integrate various AWS services such as S3 for storage and DynamoDB for database management.
  • LangChain and OpenAI: Utilize these powerful libraries to enhance your chatbot’s conversational abilities.

Project 2

MimirAI

MimirAI is an advanced chatbot project designed to help users interact with their documents more intelligently. This project leverages cutting-edge technologies to allow users to upload documents, perform queries, and receive relevant responses. MimirAI combines a NextJS frontend, an AWS Chalice backend, and various AWS services to create a comprehensive, adaptive AI assistant.

What You'll Build:

  • Document Upload and Query System: Create a system where users can upload documents and perform intelligent queries to retrieve relevant information.
  • Adaptive Chatbot: Develop a chatbot that can understand when to fetch more information and provide contextually appropriate responses.
  • Custom Function Calling: Allow the chatbot to call functions dynamically, enhancing its ability to assist users based on their queries.

Key Technologies You'll Learn:

  • Frontend with NextJS: Build a sophisticated user interface for document management and queries.
  • Backend with AWS Chalice: Develop a robust backend using AWS Chalice, a serverless framework for creating Python APIs.
  • AWS Services: Utilize various AWS services such as S3 for storage and DynamoDB for database management.
  • LangChain and OpenAI: Use these powerful libraries to create embeddings, manage a vector database, and enhance your chatbot’s conversational abilities.

Your Shortcut to Building with AI

We’ve condensed hundreds of hours of setup, learning, troubleshooting, and deployment into 4 hours of course materials, designed with real-world production in mind.

Our Generative AI Developer Bootcamp equips you with the skills and knowledge you need to build your own generative AI applications. You’ll walk away ready to ship your own AI projects confidently and efficiently.

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Course Tools

Technologies You’ll Learn to Build With

Harness the power of advanced large language models to elevate your applications. Learn to leverage these models for sophisticated natural language processing tasks and intelligent responses.

Dive into embeddings models, essential for transforming text data into numerical representations that machines can understand, enabling improved search, recommendation, and information retrieval systems.

Get hands-on experience with the latest AI tools:

  • Images (DALL·E): Create amazing images just by describing them in words.
  • Vision (GPT-4 Vision): Combine visual and language skills to build innovative applications.
  • Speech to Text (Whisper): Turn spoken words into written text with high accuracy.
  • Text to Speech (ElevenLabs): Make your apps speak with natural, lifelike voices.

Use a variety of tools to enhance your AI projects:

  • Pinecone: Manage and deploy vector databases with ease.
  • Supabase: Utilize an open-source backend service for easy data management.
  • Chroma DB: Store and retrieve data efficiently with this open-source vector database.

Understand how to build smart agents that can perform tasks on their own and interact with users.

Take advantage of the latest open-source technologies:

  • Hugging Face: Access a wide range of pre-trained models for natural language processing.
  • Falcon: Use efficient and scalable machine learning models.
  • LLaMA Models: Experiment with advanced language models for your projects.

Learn how to put your AI applications online:

  • Building a Lambda Function: Host your AI packages on AWS Lambda.
  • Hosting a Chatbot on Vercel: Deploy a chatbot easily on Vercel.
  • Hosting AI Services: Create and manage generative AI services like text and audio through AWS.

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About the Instructor

Your instructor, Shawn Esquivel, is a Full Stack Developer, who has built 20+ projects in the generative AI space.

Shawn has built production ready gen AI solutions across numerous industries from education, human resources, B2B, and many more.

Following his previous hit AI course, where he tauhgt over 2800+ students the basics of AI, he’s ready to do it again, with the latest innovations in generative AI and GPT models.
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