MAS Machine Learning for aspiring machine learning engineers

With the Master of Advanced Studies in Machine Learning, you will be able to use cutting-edge technologies to address real-world problems using artificial intelligence. You will learn how to leverage deep learning to solve complex and impactful problems.

The program at a glance

The majority of the fastest growing roles are technology-related roles. AI and Machine Learning Specialists top the list of fast-growing jobs, according to the Future of Jobs Report 2023 of the World Economic Forum (WEF).

The MAS in Machine Learning stands out with its unique blend of practical machine learning and data science methodologies, backed with direct, hands-on experience of leading technologies such as TensorFlow and Python. The program is designed to teach a well-rounded and comprehensive skill set. The program demonstrates its industry relevance by equipping students with practical and up-to-date knowledge. With its emphasis on innovation and creative problem-solving, the program primes graduates not just for a career in the tech sector, but also for leadership roles with the potential to shape the future of the industry and of technology.

Structure of Master of Advanced Studies

The MAS program has a modular structure and consists of three CAS modules and one MAS module. The final module required is the Master’s Module comprising a master’s thesis on a real-life problem from your company or based on your interests.  

Grafik MAS Machine Learning

Durch Klick auf die Grafik gelangen Sie zur Modulübersicht des MAS-Programmes

Facts

Start

Continuous

Application deadline

Continuous

Duration

24 months

Course costs

from 28'200 CHF

Course fees for the three CAS programs (each between CHF 7,900 and CHF 12,100) plus CHF 4,500 for the MAS program. Registration fee and course materials included. 5 per cent discount for HSLU premium alumni members. SVEB continuing education vouchers accepted.

Head
Information events
Degree

Master of Advanced Studies Hochschule Luzern/FHZ in Machine Learning

Type

MAS

ECTS

60

Language of instruction
  • German
  • English
Venue

Rotkreuz

Target group
  • Professionals with a background in computer science, engineering or related field wishing to upskill in AI and machine learning. 
  • Data analysts and scientists looking to deepen their expertise in advanced machine learning technologies. 
  • Software developers and IT specialists aiming to pivot or advance their careers in the rapidly evolving domain of artificial intelligence. 
  • Industry experts and technical team leaders seeking to leverage machine learning to drive innovation and efficiency in their organizations. 
  • Entrepreneurs and business strategists eager to harness the power of AI for competitive advantage. 
  • Academics and researchers intending to apply machine learning in their work to solve complex problems. 
  • Lifelong learners with a strong quantitative foundation and a passion for technology who are eager to be at the forefront of the AI revolution. 
Requirements

A tertiary education degree (ETH/university, university of applied sciences, college of higher education or other) and at least two years of professional experience after graduation (this can be in a field other than data science). A limited number of participants with equivalent qualifications and several years of professional experience are eligible for admission via a standardized admission procedure ("sur dossier" admission) - this may be subject to conditions.

Provider(s)

Computer Science and Information Technology

Methodology

Created with the professional in mind, this program offers a flexible format that allows participants to balance their work and personal commitments. Classes are taught by expert instructors capable of enhancing the learning experience by merging real-world practice with cutting-edge research. Their teaching practice is firmly rooted in practical applicability and by encouraging students to tackle real-life projects, they ensure that they are fully prepared for the workplace after completing the program. What is more, the program facilitates networking opportunities, enabling students to forge valuable connections with industry leaders, alumni, and peers.

Remarks

Specific requirements are set out for each CAS separately. There are no specific requirements for the MAS module.

The thesis can be written in both English or German. Interaction with the supervisor can be in English or German.