CAS ETH in Machine Learning in Finance and Insurance
This description is only available in English.
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Spring Semester
Start -
9 months
Duration -
ETH ZurichLocation
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EnglishTuition language
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01.11.2023–31.01.2024
Application period -
CHF 13,000
Programme fee
In brief: The CAS ETH in Machine Learning in Finance and Insurance
The programme provides of a deep understanding of the intersection between machine learning technology and applications to foster innovation in the rapidly changing financial services landscape.
Structure and content
Programme description
The CAS ETH in Machine Learning in Finance and Insurance offers a unique and engaging interdisciplinary curriculum along: A comprehensive introduction to the fundamentals of machine learning; a critical reflection on the integration of AI; deep dives into cases and applications guided by faculty and professionals in workshop formats as well as “Your innovation project” guided by a mentor from faculty or industry.
Objectives
The CAS aims to produce graduates who have a solid understanding of the intersection between ML technology and applications, including an understanding of the overall system landscape & architecture in which a ML model is embedded. Students will be able to chase after and lead the development of innovative, responsible ML solutions. Graduates will have a broader professional network through the guest speakers, mentors and community of the ETH FinsureTech Hub.
Professional perspectives
Graduates will be able to hold a senior or leadership position in technology driven projects, start their own technology-focused business, or advance their careers within their current organisation.
Structure and format
Participants complete 4 blocks over 9 months, with knowledge delivery through interactive lectures (Block I). Content and case delivery (Block II & III) will be conveyed through interactive seminars in which lecturers convey relevant content in conversation. Study workload is approximately 300 hours, including lectures, study time and performance assessments.
Additional information
The CAS will finish with “Your innovation project”: The direct feedback and review of progress on a project that you define together your mentor at the beginning of Block IV will help develop your ML competences and also allow to facilitate the application of the knowledge components.
The CAS ETH in Machine Learning in Finance and Insurance is hosted at the ETH FinsureTech Hub. The Hub bundles expertise among ETH researchers and professionals across emerging areas like data science, machine learning, cyber security, distributed ledger technology, digital currencies and quantum computing.
Tuition language(s)
English
Credits
15 ECTS credits
Target group and admission
Target group
Professionals with a science and engineering background who want to deepen their knowledge in machine learning and unlock its potential in the financial industry with minimum of two years of professional experience in finance, banking or insurance.
Requirements
Master's degree acknowledged by ETH or equivalent educational qualifications, at least two years of professional experience in finance, banking and insurance, and good command of English.
Required language skills
Englisch: B2 – external pageShow proficiency scales
Language(s) of performance assessment
Dates and venue
Start
Spring Semester 2024
Duration
9 months
Application period
01.11.2023–31.01.2024
Location
Fees
Programme fee
CHF 13,000
Application fee
CHF 50 for persons with a Swiss university degree, CHF 150 for persons with another university degree (non-refundable, credit card payment only)
Withdrawal fee
- Withdrawal within 30 days after admission and before the beginning of the programme: free of charge
- Withdrawal more than 30 days after the admission date and before the beginning of the programme: CHF 5,000
- Withdrawal after the beginning of the programme: CHF 13,000
Application
Questions about the application
ETH Zurich, School for Continuing Education, HG E 17–18.5, Rämistrasse 101, 8092 Zurich, Tel. external page+41 44 632 56 59, E-mail
Application documents
- Diploma certificate and transcript (of records) of the highest or most relevant degree
- Passport or identity card
- DownloadDeclaration of consent (PDF, 94 KB)
Organiser
Programme management
Contact
ETH Zurich
FinsureTech Hub
Florastrasse 7
SEC D2
8092
Zurich
Responsible body
ETH Zurich, Department of Mathematics, ETH Zurich (D-MATH), ETH FinsureTech Hub