Curriculum

Embrace a Supportive Learning Environment

Throughout the program, you'll benefit from collaborative learning, with courses taught jointly by esteemed professors and lecturers from UC Davis and ZHAW. Our state-of-the-art facilities provide an optimal learning environment, equipped with cutting-edge tools for streaming and recording.

Achieve Success Through Assessments and Practical Application

Your success is our priority. Throughout the program, you'll have the chance to demonstrate your knowledge and understanding through assessments and a final report on a topic of your choice. Additionally, you'll present your findings in a short video, fostering a collaborative and supportive learning environment.

Gain In-Demand Skills and Expertise

By the end of the AIDA Executive Certificate Program, you will:

• Possess a comprehensive understanding of data competence, data design, and data representation.
• Master the ability to extract insights from diverse datasets, utilizing a wide range of tools, from linear models to artificial neural networks.
• Stay ahead of the curve with the latest trends in machine learning, including emerging technologies such as large language models and generative adversarial networks.
• Enhance your forecasting skills across various fields of application, enabling you to make informed decisions and drive strategic outcomes.

Modules

Every module is jointly taught by faculty from UC Davis and ZHAW, and it corresponds to 15 hours of live lessons.

Module 1

Feb 19, 2024: Begin online video Module 1

• UC Davis: 15 hours
• ZHAW: 15 hours

March 18-22, 2024: Live Week in Zurich

• UC Davis – 12 hours (in person)
• ZHAW – 18 hours (in person)

Module 2 

April 2, 2024: Begin online video Module 2

• UC Davis: 15 hours
• ZHAW: 15 hours

May 13-17, 2024: Live Week in Davis

• UC Davis – 18 hours (in person)
• ZHAW – 12 hours (in person)

Data Competence for Leaders

Data sources, data management, data storage, and data compliance. Common data issues will also be discussed.

Data Design and Representation

Introduction to business applications involving standard, streaming, and network data. Emphasis on scalable technologies for processing and analyzing big data in diverse settings.

Driving Insights and Impact 1

Introduction to business analytics and its applications. Discussion of the ethical implications of business analytics, also to understand its limits. Introduction to methodologies and frameworks used in business analytics, including causal approaches

Driving Insights and Impact 2 (online)

Understanding how to collect, process, and quantify data. Discussion of the role of descriptive, predictive, and prescriptive analytics in business.

Machine Learning for Business 1

Supervised machine learning tools (GLM, trees, forests, SVM) with a stress on the pros and cons of the different models, applicability, and discussion of case studies.

Machine Learning for Business 2 (online)

Unsupervised machine learning tools (neural networks, deep learning, clustering) with a stress on the pros and cons of the different models, applicability, and discussion of case studies.

Applied Forecasting (online)

Models and tools to forecast, with applications in finance, business, energy markets, epidemiology, and social behavior.

Specialized Applications (online)

Participants will be asked to express their preferences for a selection of specialized applications, including but not limited to fraud detection, blockchains, advanced data quality issues, financial services applications, decentralized finance, customer analytics, marketing, and dealing with the unknown.

Evaluation

At the end of every week, there will be a written exam.

To obtain the final ECTS certificate, participants will also be asked to write a final report on a topic of their choice, among those discussed in the different modules. Upon completing the course, all participants will receive an Executive Education Certificate from UC Davis. 

A short 10-minute video in which they present and discuss their findings is also expected. All videos will be shared on the course platform for mutual feedback.