AI 501: AI Tools for Coders

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Overview

With AI revolutionizing software creation, developers and dev teams need new skills and strategic retooling.

This course addresses these evolving challenges by empowering coders with the mastery of cutting-edge AI tools and preparing teams for accelerated product development. Implementing the right tools and workflows leads to improved code quality, faster results, and happier devs. You'll learn how to integrate LLM technology effectively in your projects, while also recognizing its limitations and navigating potential licensing pitfalls.

Enroll now to confidently navigate the AI-driven future of software development, enhancing your individual capabilities and bolstering your team's organizational prowess.

Outcomes

By the end of this course, participants will:

  • Gain an understanding of how LLM-based tools can make coding more effective and enjoyable.
  • Learn how to integrate AI effectively in your coding practice and get the most out of it.
  • Understand the limitations of AI in coding, including institutional concerns, policy and legal aspects, and technical limits.
  • Enhance your ability to perform core coding functions with AI support, such as code writing, testing, accessibility, code review, and security checks.

Prerequisites

  • This course is designed for developers with a basic understanding of coding and software development. Familiarity with AI concepts is helpful but not mandatory, as the course will cover fundamental aspects of AI tools and their application in coding.
  • Participants also need a (free) chatbot account, with a service like ChatGPT, or Google Bard.

Topics

The course covers a wide range of topics, including:

  • How GPTs work and their application in software development.
  • AI's role in code writing, testing, accessibility, developer workflows (eg: code reviews, security checks), and more.
  • Using AI for other tasks like image generation and CLI jobs.
  • Building AI-powered apps with the OpenAI API, including practical modules on vector databases and data privacy.
  • Understanding and navigating license requirements, bias amplification, and reliability of AI outputs.
  • Developing complementary skills such as communication, judgment, and decision-making to enhance AI integration in coding projects.

Learn with Stacked Modules

Concepts in each of our courses are taught using stacked modules, where a new concept is introduced in each class session, building upon what came before it. This is a challenging style that requires persistence, practice, and collaboration, but allows more concepts to be introduced over the length of the course. This method helps students learn and retain more information in a short period of time. Learn more about stacked modules »

Computer Requirements

You are required to supply your own computer that meets the requirements specified in our FAQ.