MAS Programme
Providing a targeted technical education in digital technology to advance the careers of industry managers
Organisations are changing rapidly to become more digital. With this transformation come both new challenges and new opportunities. Businesses must build interdisciplinary teams to transform software, networks and digital technologies into business applications and platforms. In offering services, companies must also manage significant concerns such as protecting privacy and avoiding bias while using artificial intelligence. Managers without any formal training in these areas need to make critical resource allocation and operational decisions that can have significant impacts on the company's profits and competitiveness. The risks and rewards of this decision making have never been higher. This is where the Master of Advanced Studies in AI and Digital Technology (MAS AID) comes in.
The MAS AID is a targeted technical programme designed for managers who want a better understanding of machine learning, artificial intelligence, cybersecurity and other digital technologies that are rapidly transforming their industry. The aim of the MAS AID is to improve their ability to communicate and collaborate with technology teams and to advance their careers in an increasingly digital world.
The target audience for this program includes managers with business, economics or similar non-technical degrees as well as people with technical degrees outside of computer science. No prior programming experience is needed.
Graduates will be able to communicate better and develop stronger relationships with IT, software and AI teams. Graduates also will be able to think deeper and more strategically about technology. In turn, this will enable them to extend their existing management skills to take on more challenging leadership roles in interdisciplinary projects and corporate initiatives with significant AI and digital components.
Programme Structure
The MAS AID is divided into two parts. The first part consists of three CAS programmes that can be followed independently or as part of the MAS. Each CAS provides science and technology fundamentals in a different area of computer science. The fundamentals are necessary to prepare participants for the more advanced material covered later and, therefore, all three CAS must be completed before starting the second half of the MAS programme.
A schedule with specific dates is usually posted on each programme's webpage approximately 3-4 months before the start. A detailed explanation of each CAS is also available on the CAS webpage:
The second part of the MAS consists of an in-depth AI Project, Cyber Security courses, and seminars covering areas such as the latest research and industry developments, ethics, industry challenges (e.g. explainable AI) and other relevant issues. These courses run concurrently over a six month period. After this, participants write a thesis on a topic of their choice developed in consultation with a thesis supervisor, typically an ETH professor or researcher/lecturer.
Courses are generally conducted in either a block format or blended learning format to minimize time away from work. Classes are usually held at ETH Zentrum campus every other weekend. Each "weekend" consists of one full day (Friday) and one half-day (Saturday morning). Thus, this programme is well suited as a part-time study programme.
Note: the curriculum is reviewed every year to ensure continuous improvement and relevance. As such, the programme content may vary from year to year, especially for the seminar topics.
Practical Experience and Skill Development
The best way to understand a technology is to learn both the theory and the practical implementation together. Throughout the program, we give participants hands-on experience in coding and implementing digital technologies through exercises and projects in addition to teaching the underlying concepts. Foundational skills developed in initial CAS are deepened further in the second half of the programme:
AI Project
The AI Project is intended to give participants a much deeper insight into the end-to-end process of developing and implementing an AI application or solution by working in teams to address real world data challenges provided by industry partners and ETH researchers. In addressing these more difficult problems, participants will gain a greater appreciation for what works and does not work when implementing AI in the real world as well as the opportunities for AI in the near future.
Cyber Security
We will provide an introduction to the fundamentals of cyber security targeted at decision makers who want to understand how cyber security threats can impact their organization, and how they can improve their security posture. Participants will gain an appreciation of the complexity and challenge of building and maintaining secure information systems in a rapidly evolving digital world with advanced persistent threats (APTs), increasingly sophisticated attacks, and mounting costs.
All technical topics will be accompanied by real world examples to showcase their usefulness and by practical exercises providing hands-on experience in applying foundational cyber security principles that will have long term utility even as the technological details change. The goal is to prepare participants to navigate the quickly changing cyber security landscape in their specific work environment.
Master Thesis
Participants will prepare an independent master’s thesis that allows them to explore a specific area of science and technology that is relevant to their work or personal interest. The thesis topic is freely selectable and can incorporate practical skills such as coding, but it must be approved in advance by the thesis supervisor. Although the thesis may incorporate policy, market information or other types of material to provide context, the final product must be sufficiently rigorous from a science & technology perspective and should be integrative of the material and skills learned during the programme.
Questions
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