CAS Cloud & Mobile Computing
Providing a targeted technical education in cloud, mobile and edge computing with AI to advance the careers of industry managers
As organisations become more digital and incorporate AI, they are also becoming increasingly dependent on networks to transform data into value. Even seemingly simple decisions such as whether to keep data storage and processing in house or in the cloud can have significant implications. Managers without any formal training in these areas are at a disadvantage when making critical resource allocation and operational decisions that can have significant impacts on corporate competitiveness. This is where the Certificate of Advanced Studies in Cloud and Mobile Computing (CAS CMC) comes in.
The CAS CMC provides a targeted education in wireless networks, communication and cloud & edge computing with AI to business managers to advance their career. The aim of this programme is to improve the decision-making of managers by providing them with fundamental training in communication technologies and the implementation of AI related business applications over wide area networks.
The target audience for this program is managers with any educational background and a minimum of five years of professional experience who need to make technology-related decisions in their companies. It is appropriate both for people with non-technical backgrounds (business, economics, etc.) and for people with technical backgrounds who have gaps or want to refresh their knowledge with fundamental technical training in these areas.
Graduates will be able to communicate better and develop stronger relationships with IT and AI technical teams and staff, particularly in relation to implementing AI applications that interact with external environments over networks. In turn, this will enable them to extend their existing management skills to take on more challenging leadership roles in interdisciplinary projects with significant AI applications.
Prior programming experience is not required but would be helpful in getting the most out of the CAS CMC. If you are also looking at our other CAS and trying to decide which one to follow first, please read our guidance on the CAS Programmes overview page.
Course descriptions
The objective of the course is to learn the fundamentals of networking and wireless communications, including physics, frequency spectrum regulation, and standards. The most up-to-date standards used for Wi-Fi, Bluetooth, Cellular 5G Satellite, Visible Light and Audio Communication Networks are reviewed and the general principles explained. Insights from various industries are shared, including the telecommunications, toy and medical technology industries.
- Introduction and Wi-Fi
- Wireless Basics (Signal, Noise, Antenna, Modulation / Coding, Fourier, Regulation)
- Networking Standards and Architectures
- Visible Light and Audio Communication, Delay Tolerant Networks
- Internet of Things (Consumer Electronics, Interactive Toys)
- Practical experiments with Python, embedded systems, and Jemula802
The objective of this course is to provide a systems view of cloud computing through a data management lens and its practical implications on everyday business. The course will give participants a better understanding of how infrastructure, architecture and software work together to provide a valuable service, and then will show how cloud computing is changing with the increasing use of AI. We will also explore how selected newer technologies, some driven by the needs of AI, are poised to have a significant impact on cloud operations and usage in the future.
Potential topics (subject to change) include:
- Physics/infrastructure of the cloud: compute, storage, networking and power.
- Geography of the cloud: locality of cloud regions, high availability, connectivity, caching, and data sovereignty.
- Economics of the cloud: utility for computing power or just someone else's computers; capital or operating expense.
- Scalability of the cloud: elasticity of resources and automation of all management operations.
- Practical case studies: netflix, gmail, facebook, global bank application.
- Hands-on data processing: excel, local database, provisioned and serverless cloud database.
The objective of the course is to learn about the general principles of mobile computing and computing in edge devices where network connectivity is not assured and computing resources are constrained. Participants will work with electronic devices and software simulators to better understand how data processing and A.I. assisted decision-making works and also fails under real world conditions. Insights from various industries are shared, including the telecommunications, toy and medical technology industries.
- Signal Processing and Time Series, Feature Detection, Correlation, Machine Learning
- Dynamic Spectrum Assignment with Reasoning
- Spectrum Regulation, Open Access, Multi-Stage Games
- Fine Tuning and Using an A.I. Large Language Model (LLM) for Decision-Making
- Mobile and Edge Computing
- Practical experiments with Python, Jemula802, Local LLM
This course is still under development and subject to change. The planned course offers a practical, hands-on exploration of the dynamic world of building products powered by (generative) AI. After establishing a foundational understanding of core machine learning principles, we will delve into the specifics of generative AI models and AI agents, highlighting their unique capabilities and challenges.
Students will gain insights into the entire lifecycle of AI product development, including understanding user needs, designing AI solutions, selecting appropriate technologies, and managing deployment challenges.
Through case studies and interactive exercises, participants will develop the skills to identify opportunities, build prototypes, and ultimately launch successful generative AI products. The course combines theoretical knowledge with practical applications, preparing students to create innovative AI-driven solutions.
Additional information
Participants complete 4 modules over 4 months. Courses are conducted in block format to minimize time away from work. Classes are held at ETH Zentrum campus on seven weekends, each consisting of one full day (Friday) and one half-day (Saturday morning). Thus, this CAS is well suited as a part-time study programme.
Workload is approximately 300 hours.
Study language is 100% English.
CAS CMC applicants must satisfy the following requirements:
- ETH recognised university degree at Master level or equivalent educational background
A bachelor degree can be exceptionally considered sur dossier.
- Demonstrated managerial experience
At least 5 years of professional work experience that includes some experience with allocation of corporate resources, e.g. line management, project management, etc.
- Good knowledge of English
At least B2 level is recommended.
MAS AID participants and applicants have priority over CAS only applicants. Prior completion of the CAS in Data & Machine Learning (CAS DML) and CAS in AI and Software Development (CAS AIS) is recommended, but not required. In particular, programming experience equivalent to completing both the CAS DML and CAS AIS is highly recommended. Preference in admissions is given to applicants that have completed the CAS DML and CAS AIS or have some basic knowledge of programming and computer science that would make following this CAS more beneficial for the participant.
Applications will be reviewed by the Admission Committee. The final decision is communicated by the School for Continuing Education.
Applicants will receive an email notifying them when the admission decision letter is available for download in their eApply account. Admitted applicants do not need to confirm their intention to participate in the programme. A separate email will be sent with instructions on how to set up their ETH email and access their ETH student account (myStudies). All subsequent communication will be via the ETH email account.
To withdraw, the admitted participant must notify the School for Continuing Education by email (). Withdrawal is subject to the following fees.
- Free of charge: within 30 days from the date of the admission decision letter and before the beginning of the programme.
- CHF 3,500: more than 30 days after the admission date and before the beginning of the programme.
- CHF 8,500: after the start of the programme.
The CAS CMC tuition fees and ECTS can be fully credited towards the MAS in AI and Digital Technology. Successful graduates of the CAS CMC who wish to continue can apply to the MAS in the same manner as any other applicant. Prior completion of CAS will be considered during the application review, but there is no automatic right of admission to the MAS after completing individual CAS programmes.
Questions
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