CAS Cloud & Mobile Computing

Providing a targeted technical education in mobile computing and AI products to advance the careers of industry managers

As organisations become more digital and incorporate AI, they are increasingly developing AI products for use over networks and on mobile devices to transform data into value. Even seemingly simple product decisions can trigger difficult technical tradeoffs. Managers without any formal training in these areas are at a disadvantage when making 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, mobile computing and AI product development 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, law, social sciences, 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

This course provides foundational knowledge of data networks and wireless communications, focusing on current networking standards, radio physics, and regulations. It also reviews today's standards for Wi-Fi, Bluetooth, Cellular 5G, Satellite, Visible Light, and Audio Communication Networks, and explains the general principles behind them. The course also shares industry insights from the telecommunications, toy, and medical technology sectors.

From Analog Signals to Digital Data: Data Sampling, Quantization, Nyquist Criteriai
Redundancy, Entropy, Compression, Coding
Fourier Transform, Frequency Representation and Shannon Capacity
Wireless Basics: Path Loss, Noise, Interference, Modulation, Coding, Link Budget
Data Networking Standards, Wi-Fi, 5G, Starlink
Visible Light and Audio Communication, Internet of Things, Mesh Networks
Practical experiments with Python, embedded systems, Jemula802, and Jupyter Notebooks

Designed for professionals and managers ready to move beyond basic experimentation, the module bridges the gap between raw generative power and strategic product execution. We explore the paradigm shift from manual software craftsmanship to AI driven product orchestration, where the role of the innovator evolves from writing syntax to defining high level intent.

The core methodology focuses on mastering Prompt Engineering as a rigorous technical specification, treating intent as a formal contract rather than a casual interaction. After exploring the emerging world of Vibe Coding where high level intent replaces manual syntax, the focus shifts to AI Use Case Design. This strategic phase allows participants to identify high impact, AI native opportunities and evaluate them through a dual lens of technical feasibility and long term business value.

This foundation leads directly into the Liquification of Software, a world where applications are generated, iterated, and discarded at the speed of thought. Through hands on sessions with cutting edge tools like Claude Code, students transition from simple chat interfaces to commanding terminal based agents. By mastering the Agentic Loop, participants learn to delegate entire feature sets to AI, effectively redefining the modern engineering workflow for professional grade systems.

This course explores the fundamentals of mobile computing in environments with limited or unreliable network connectivity and constrained computing resources. Participants will gain hands-on experience with electronic devices and software simulators to understand data processing and the successes and failures of mobile A.I. decision-making in real-world scenarios. The course also features insights from various industries, including telecommunications, toy, and medical technology.

P.I.D. Controllers
Mobile A.I. - Working with resource-constraint local LLMs
Simple chain of thought reasoning
Using Mobile A.I. for decision-making
Frequency usage as multi-stage games, competition
Practical experiments with Python, Jemula802, Jupyter Notebooks

This course is still under development and subject to change. The planned course will explore the integration of GenAI into cloud and mobile computing, learn how to prioritize GenAI use cases, define operational prerequisites for successful deployment, and set governance strategies to ensure responsible GenAI implementation.

Additional information

Download CAS CMC Fall 2026 Class Schedule (PDF, 185 KB)

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.

Please apply online through the School for Continuing Education website. After submitting the application and uploading supporting documentation, you will be asked to pay the non-refundable application fee of CHF 50 or CHF 150 depending on where you obtained your degree.

Application period: 1 May - 1 June (Fall start)

The tuition fee is 8,500 CHF and includes costs for software licenses, materials, etc. There are no other fees.

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.

Programme Director