Build an AutoGPT Code Writing AI Tool With Rust and GPT-4

Build an AutoGPT Code Writing AI Tool With Rust and GPT-4, available at $99.99, has an average rating of 4.71, with 132 lectures, 1 quizzes, based on 395 reviews, and has 3952 subscribers.

You will learn about Master the Rust programming language from zero to hero Understand how to leverage GPT-4 (ChatGPT) to build your own AutoGPT using Rust Understand how to build AI functions for structuring exact desired responses from LLMs (large-language-models) Build your first web server using the Actix Web framework in Rust Build an AutoGPT that not only writes any code you like, but tests, improves and re-writes where necessary This course is ideal for individuals who are Enthusiastic or intermediate programmers who want to learn Rust or Programmers who want to build their own blazingly fast and memory-safe AutoGPT models or Startups who want to give their developers a blue print to building cutting-edge AI solutions It is particularly useful for Enthusiastic or intermediate programmers who want to learn Rust or Programmers who want to build their own blazingly fast and memory-safe AutoGPT models or Startups who want to give their developers a blue print to building cutting-edge AI solutions.

Enroll now: Build an AutoGPT Code Writing AI Tool With Rust and GPT-4

Summary

Title: Build an AutoGPT Code Writing AI Tool With Rust and GPT-4

Price: $99.99

Average Rating: 4.71

Number of Lectures: 132

Number of Quizzes: 1

Number of Published Lectures: 132

Number of Published Quizzes: 1

Number of Curriculum Items: 133

Number of Published Curriculum Objects: 133

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Master the Rust programming language from zero to hero

Understand how to leverage GPT-4 (ChatGPT) to build your own AutoGPT using Rust

Understand how to build AI functions for structuring exact desired responses from LLMs (large-language-models)

Build your first web server using the Actix Web framework in Rust

Build an AutoGPT that not only writes any code you like, but tests, improves and re-writes where necessary

Who Should Attend

Enthusiastic or intermediate programmers who want to learn Rust

Programmers who want to build their own blazingly fast and memory-safe AutoGPT models

Startups who want to give their developers a blue print to building cutting-edge AI solutions

Target Audiences

Enthusiastic or intermediate programmers who want to learn Rust

Programmers who want to build their own blazingly fast and memory-safe AutoGPT models

Startups who want to give their developers a blue print to building cutting-edge AI solutions

Develop a an automated ChatGPT agent which not only writes code, but tests and re-write code for you. In fact, you can request your agent to do just about anything.

By going through this course, you will not only learn and master Rust from A-Z, but you will also have extensive knowledge in how to build your very own AutoGPT.

The name of the AutoGPT we build together will be Auto-Gippity.

Auto-Gippity will simply be given a task, which it will break down and delegate to other agents to complete. Each agent will be responsible for testing its own output.

Our test piece will be to build an agent that writes a web server given a template. It will write the code in Rust. Not only that, but we will write the agent, that writes Rust codein Rust. Fantastic. What a time to be a developer.

AutoGPTs will only continue to become extremely relevant and highly sought after and combining these with the worlds favourite programming language, Rust, means that we can build an application which is blazingly fast, memory-safe, modern and robust.

Right now, there is a window of opportunity to learn this fantastic and uncommon technology before it takes over in software engineering.

Just think, you could build an AutoGPT that say, develops full stack SAAS websites end-to-end. With technologies like GPT-4 and soon beyond, such agents will only continue to improve in their performance.

Companies are looking for developers who can build such tools and SAAS startups have a window to be first. If you are curious as to how you can connect new AI technologies to change the world then THIS is the course for you.

You will learn:

How to work with the Open AI API and the GPT-4 API using Rust

How to master rust from A to Z, progressing from beginner, to intermediate, to advanced and beyond

How to build AI functions (special functions that extract a desired response from large-language-models)

How to develop a web server template (including an introduction to web servers) using Actix Web

How to build an Automated GPT agent (Auto-Gippity) which writes code, that executes and tests code. If the code is wrong, it will simply re-write it and test again

We are truly excited to see what you develop, so make sure you share your application with the world.

See you in class!

Shaun

Course Curriculum

Chapter 1: Introduction

Lecture 1: What We Are Building

Lecture 2: Programming Experience Required

Lecture 3: About Your Instructor

Lecture 4: Discord and Q&A

Lecture 5: Getting Access to GPT-4

Lecture 6: AI Functions and LLM Limitations

Lecture 7: Course Structure Overview

Lecture 8: IMPORTANT: RESOURCES

Chapter 2: Rust Crash Course – Learning the Rust Environment

Lecture 1: Rust installation – Quick Walkthrough

Lecture 2: Rust Installation – Windows Docs

Lecture 3: About Rustup

Lecture 4: Rustup Tool Manager Docs

Lecture 5: Preparing Visual Studio Code

Lecture 6: Cargo New – Your First Rust Project

Lecture 7: Your First Rust Function

Lecture 8: A Brief Programming Language Comparison

Lecture 9: Structuring Project Modules – Brief Introduction

Lecture 10: Unit Testing with Cargo

Lecture 11: Create Docs with Cargo

Lecture 12: Creating a Rust Library

Lecture 13: Dead Code and Unused Variables

Chapter 3: Rust Crash Course – Types and Memory Management

Lecture 1: Must-Know Resources

Lecture 2: Rust vs Other Languages Revisited

Lecture 3: Integer Types

Lecture 4: Data Type Cheatsheet

Lecture 5: Stack vs Heap Intro

Lecture 6: Stack Deep Dive

Lecture 7: Stack vs Heap Walkthrough

Lecture 8: String Literals and Static (Read-Only) Memory

Lecture 9: Ownership and Borrowing – Immutable References

Lecture 10: Ownership and Borrowing – Mutable References

Lecture 11: Ownership and Borrowing – Dereferencing

Lecture 12: About Scope

Chapter 4: Rust Crash Course – Basics

Lecture 1: Intro – Create Project

Lecture 2: Fixed Size Variables

Lecture 3: Dynamic Sized Variables

Lecture 4: Basic Collections

Lecture 5: Closures

Lecture 6: Number Literals and Raw Strings

Lecture 7: Working Low Level with Binary

Lecture 8: Rust Std Library

Chapter 5: Rust Crash Course – Intermediate

Lecture 1: Intro – Create Module

Lecture 2: Enums – Your First Enum

Lecture 3: Enums – Result Enum with Generics Introduction

Lecture 4: Enums – Option Enum with Some or None

Lecture 5: Rusts Result and Option

Lecture 6: Structs – Your First Struct

Lecture 7: Structs – Using Type Impl

Lecture 8: Traits Introduction

Lecture 9: Polymorphism with Traits and Generics

Lecture 10: Lifetimes – Introduction

Lecture 11: Lifetimes – Generics and Structs

Lecture 12: Pattern Matching – Integer, Option and Result

Lecture 13: Pattern Matching – Mixed Data Enum

Lecture 14: Pattern Matching – Match Guards and Structs

Lecture 15: Your First Async API Call

Lecture 16: Handling Errors

Lecture 17: Collections Revisited – HashMaps and HashSets

Lecture 18: Project Cleanup

Chapter 6: Rust Crash Course – Advanced

Lecture 1: Declarative Macros – Introduction

Lecture 2: Declarative Macros – With Repetitions

Lecture 3: Declarative Macros – Note on Module Exporting

Lecture 4: Procedural Macros (Theory) – Introduction to Derive

Lecture 5: Procedural Macros (Theory) – Function Like Macro

Lecture 6: Procedural Macros (Theory) – Attribute Like Macro

Lecture 7: Procedural Macros (Practice) – Building an AI Function

Lecture 8: Smart Pointers – Box

Lecture 9: Smart Pointers – Reference Counting with RefCell

Lecture 10: Smart Pointers – Reference Counting with Weak

Lecture 11: Rust Concurrency with Mutex and Arc

Lecture 12: Publish Packages to Crates

Chapter 7: Build Web Server Template – First Project

Lecture 1: Theory – Introduction to Web Servers and Actix Web

Lecture 2: Theory – Actix Web REST API Docs Walkthrough

Lecture 3: Project Setup

Lecture 4: Struct Definitions

Lecture 5: Database Implementation

Lecture 6: Creating AppState with Mutex Provided Safety

Lecture 7: Writing Our Initial Web Server

Lecture 8: Testing Create Task Rest API Endpoint With Postman

Lecture 9: Create and Test GET Task Request

Lecture 10: Complete Task CRUD

Lecture 11: User Registration and Login

Lecture 12: Mutation Adjustment

Lecture 13: Next Steps

Chapter 8: Auto GPT Project – Supporting Functions

Lecture 1: Supporting Functions – Section Introduction

Lecture 2: Project Setup

Lecture 3: User Interaction with Command Line

Lecture 4: Extract API Keys

Lecture 5: OpenAI Call – Key Provisions

Lecture 6: OpenAI Call – Create Client

Lecture 7: OpenAI Call – Test API Call

Instructors

Shaun McDonogh
Lead Analyst and Full Stack (Python and React) Developer

Rating Distribution

1 stars: 2 votes

2 stars: 3 votes

3 stars: 21 votes

4 stars: 92 votes

5 stars: 277 votes

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