AI: Realizing Opportunities

This course is aimed at employees, who have an interest in artificial intelligence and machine learning, and managers, who want to supervise data science projects.

• You will get an overview of the topic of artificial intelligence.
• You will understand which problems can be solved with machine learning and the steps in a typical ML project.
• You will learn how to identify ML use cases with business impact.
• You will better understand the challenges and risks of ML applications.

The course is based on my book A Practitioner's Guide to Machine Learning, which you can refer to for more details.

Prerequisites

• Good command of the English language (all materials are in English)
• Basic understanding of math (at high school level)
• Have fun puzzling and an interest in new technologies
• Complete the Preparation part before the first group session (about 20min; see below)

Preparation before the course (~20min)

• Read the first chapter of the book: "Introduction"
• Think about where in your daily life you're already using machine learning (in addition to the provided examples)

Course (9:00-17:00)

Welcome:

• Orga & Introduction round: Where are you using ML?

Lecture:

• What is ML?
• How do machines “learn”?
• ML use cases

Exercise:

• Industry Spotlights: Recognize ML solutions

Lecture:

• Solving problems with ML

Lunch Break (ca. 12:00-13:00)

Exercise (Part 1):

• Identify opportunities how ML could be used to improve a given process

Lecture:

• Garbage in, Garbage out!
• Models can discriminate
• Adversarial Attacks

Exercise (Part 2):

• Assess the identified ML solutions with respect to different risks

Good Bye:

• Conclusion
• Feedback