Taught course

Data Science, AI & Digital Business

Institution
GISMA Business School
Qualifications
MSc

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Entry requirements

Entry requirements

• Bachelor’s degree in relevant scientific discipline

• English proficiency: B2 (IELTS 6.0) or equivalent

• For non-standard entry routes please seek clarification on requirements with our admissions team.

Months of entry

January, April, June, September

Course content

This unique combination of technology and business which will help you keep a competitive advantage in the job market and advance into a future-oriented career in a global company or innovative start-up.

Digital technologies are omnipresent in today's society and business world. All areas of life are affected by a digital revolution which is evolving faster and faster. Artificial intelligence, 5G, Big Data, the Internet of Things, and Blockchain will disrupt traditional business models. Job roles will change.

Study the MSc in Data Science, AI, and Digital Business to be prepared for this change Become an expert in data science and AI by mastering machine learning, big data analytics, methods of prediction, and leadership of virtual teams. This programme also covers general business skills such as project and innovation management, which will boost your employability.

You will benefit from a highly international atmosphere by studying at GISMA Business School in the Berlin area, in close proximity to global companies such as Tesla. If you study the 2-year programme you’ll also have the opportunity to do an internship or business project or spend a semester abroad – choose from a selection of leading technology hubs such as London, Shanghai, and Singapore.

Accreditations and rankings

GISMA Business School also has a long history of working with partner universities in Europe and has successfully delivered partner programmes accredited by AACSB, AMBA, EQUIS, and EPAS.

Who is the programme for?

The programme is perfect for those with undergraduate degrees in engineering, data science or technology-related sciences who seek to specialise further in this field. It is also perfect for graduates of other complementary scientific disciplines such as business, economics, law, social sciences, or psychology, who are interested in pursuing a data-related career path. This programme is also suitable for anyone who has work experience in data science and AI and wishes to advance their career with a postgraduate degree.

What will you learn?

This programme covers multiple aspects of data science and AI, from machine learning to big data analytics and ethics in AI. You will also work on your leadership skills and digital business competencies such as digital marketing and innovation management. With this diverse and valuable skillset, you will be an asset to any future-oriented company.

How will you study?

GISMA Business School supports flexible and individual learning by applying a systematic hybrid learning scheme.

You will spend part of your lectures in class at our Berlin-Potsdam campus. These face-to-face phases are complemented by e-learning sessions. You will work on cases, reflect on readings, take part in online discussions, and participate in group exercises and projects. This variety of learning methods is part of our unique teaching strategy, which includes student-centred pedagogy, project-based learning, collaborative learning, and personalised coaching.

You can start working on your master thesis after you have earned two thirds of the total programme credits. The thesis takes three months in the 1-year programme and six months in the 2-year programme.

Fees and funding

UK students
€13,000
International students
€15,500

1-year programme

EU fee - € 13,000 / Year

International fee - €15,500 / Year


2-year programme

EU fee - € 11,000 / Year

International fee - €12,500 / Year

Qualification, course duration and attendance options

  • MSc
    part time
    24 months
    • Campus-based learningis available for this qualification
    full time
    12 months
    • Campus-based learningis available for this qualification

Course contact details

Name
GISMA