What is AI?

Why Use AI in Government?

  • Artificial Intelligence (AI)

    The study of the broader class of algorithms and techniques used to model human-like intelligent behavior in computers.

  • Machine Learning (ML)

    A branch of AI that focuses on using math and statistics to allow for computers to automatically learn through training data.

  • Reinforcement Learning (RL)

    A branch of AI and ML that aims to learn how to take optimal actions in some system to maximize the cumulative reward.

Who is this Course for?

Make sure you're in the right place.

  • Beginner to Artificial Intelligence, Machine Learning, and Reinforcement Learning

  • Minimal technical fluency | No STEM / Computer Science degree required

  • Government executives trying to understand how to use Artificial Intelligence (AI)

  • Government contractors wanting to learn how to integrate AI into their offering

  • Startups trying to understand how to work with government on AI, ML and RL

AI for Government

The Next Frontier

  • Autonomous Public Transportation

    Imagine truly autonomous public transportation with 100% up-time. With advancements in deep reinforcement learning and computer vision.

  • Intelligent Legal Analysis

    Use Natural Language Processing techniques to autonomously intelligently analyze hundreds of pages of legal documents and the various effects.

  • Augmented Homeland Security

    Use artificial intelligence techniques like computer vision and deep learning to detect high dimensional suspicious patterns to protect our nation's most important assets.

Artificial Intelligence for Government | Pricing

Artificial intelligence has the chance to revolutionize the public sector. We believe access to these fundamental skills shouldn't be a privilege.

What will you Learn?

By the end of this course you will...

  • Understand the current AI landscape

  • Understand what and what isn't realistic in AI

  • Understand the fundamentals of ML and RL

  • Understand applications of computer vision

  • Understand applications of natural language processing

  • Understand applications of robotics

  • Understand ethical concerns of AI

  • Understand challenges in data collection and handling