AI and Data Science

Course overview

The amount of information humans can manually process is limited. As a result, business leaders have traditionally relied on a small set of data to make decisions. However, as data volumes grow in the Technovate Era, the approach to problem-solving is shifting, with computers and algorithms playing a larger role. Artificial intelligence, including machine learning, is central to this shift.

Looking back in history, Japan’s civil war era marked a revolution in battle tactics, where swords were replaced and surpassed by guns. AI holds a similar transformative power today, and the key question for modern business leaders is how to harness it effectively.

In this course, students will learn essential data science concepts that can help business leaders make efficient use of machine learning and predictive AI. Once students understand how machines are trained, they will explore generative AI, which is reshaping the way we interact with computers.

Students will gain hands-on experience in data processing and examine popular machine learning algorithms to build predictive models for various data types. Traditionally, data science – especially deep learning and other mainstream machine learning methods – has required proficiency in programming languages like Python and R. This has been a barrier for business leaders without engineering backgrounds. However, new tools are making data science more accessible, allowing more leaders to leverage machine learning and pave the way for AI applications.

By using these tools, engaging in hands-on activities, and experiencing the data science process, we aim to achieve the following.

• Understand the implications of AI and data science, including what they can and cannot do
• Set appropriate challenges for applying AI and data science.
• Learn to ask the right questions of data scientists and interpret key results effectively

This course is intended for students who want to understand machine learning, gain hands-on experience with the data science process and learn how to use AI to develop their business.

No prior knowledge of data science or machine learning is expected. To enhance the learning effect, students should have completed the courses listed below or possess the equivalent knowledge. You will also be expected to perform cross-tabulation (pivot tables) on Microsoft Excel for exploratory analysis of data. If you don’t know how, please look it up on the Internet before class. There are also resources on GLOBIS Unlimited for your reference.