Artificial Intelligence (AI) 101 – Principles and Applications

June 19, 2020 0 Comment


SKU: course-5 Category:



Artificial Intelligence (AI) is the ability of a computer program to learn and take action. The advantages of AI applications are enormous and can revolutionize any professional sector.

 From SIRI, Alexa, Google assistant to self-driving cars, AI is progressing rapidly. Often times science fiction portrays it as robots with human-like characteristics. AI can encompass anything from Google’s search algorithms to IBM’s Watson to autonomous weapons.

 Artificial intelligence today is designed to perform a narrow task (e.g. only facial recognition or only internet searches or only driving a car). This is known as narrow AI. However, many researchers have a long-term goal to create general AI. While narrow AI may outperform humans at whatever its specific task is, like playing chess or solving equations, general AI would outperform humans at nearly every cognitive task.

 “Everything we love about civilization is a product of intelligence, so amplifying our human intelligence with artificial intelligence has the potential of helping civilization flourish like never before – as long as we manage to keep the technology beneficial.“ –Max Tegmark, President of the Future of Life Institute

Course Description

Welcome to Artificial Intelligence (AI) 101 – Principles and Applications! This is a 4-day interactive training course. In this course, you will learn the logic behind AI by tracing its history and discussing how it’s being used today. You will learn the basic principles of AI and when and how to apply it. Together we will experiment with some fun and practical examples of AI. Join us to learn how this emerging technology has the potential to transform your business.


  • An open mind and a willingness to learn
  • No coding experience required
  • A laptop computer with a webcam and the chrome browser


By the end of the course, you will be able to:

  • Explain AI concepts and its main terms
  • Identify good problems for machine learning to solve
  • Frame your own machine learning problem that is ready for execution
  • Gain a solid grasp of the state of AI today and where it is headed in the future
  • Understand the skills needed to succeed in the field of AI


  • Business executives interested in the impact of AI on business and how it will create disruption in different industries
  • Practitioners looking for a practical introduction to AI and how to start a career in this new and exciting field


Module 1: Introduction and History of AI

  • Using Data = Training
  • Answering Questions = Prediction
  • Making sense of a messy world
  • Solving Problems: Big and Small
  • History of AI
  • Fun Interactive Examples
  • Terms and Definitions
  • Course Project Introduction

Module 2: Machine Learning (ML) Problem Framing

  • Describe examples of products that use ML
  • Identify whether to solve a problem with ML
  • Compare and contrast ML to other programming methods
  • Apply hypothesis testing and the scientific method to ML problems
  • Discuss ML problem-solving methods

Module 3: It’s all about the Data

  • Data Sources
  • Data Preparation
  • Good Data Analysis
  • Publicly Available Datasets
  • Earth Engine Data Catalog
  • Google Dataset Search
  • Kaggle Datasets
  • APIs and Web Scraping

Module 4: Responsible AI Practices, Tooling, and Case Studies

  • Google’s Principles
  • Various Industry Case Studies
  • AI tooling
    • Technologies: R, Python, Spark, Hadoop, etc.
    • Platforms: Microsoft Azure, IBM Watson, Google Tensorflow, etc.
    • AutoML
  • Next Steps and further learning
  • Course Project Presentations
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