Master of Science in Data Science, Machine Learning and AI in Rushford Business School | Fees, Eligibility and More

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Switzerland

Master of Science in Data Science, Machine Learning and AI

Switzerland

Rushford Business School

Geneva, Switzerland

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About Course


Key information
Duration
: 18 Month
Study Type
: Full Time
Tuition fees
: 17500 CHF / Per Year
Conditional Scholarship
: NA
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Data science has emerged as the fastest-growing career field in the past decade. Irrespective of the nature of the industry, data science has cultivated entirely unconventional ways of looking at and working with data, guided by standard statistical and mathematical principles. What is fascinating are the deep insights we gain with this—"data is the new fuel," as it is commonly known.

Data science and machine learning are buzzwords that go hand in hand. This one-of-a-kind MSc programme is a blend of data science, machine learning, and artificial intelligence to enable students' business decision-making and analytics. This M.Sc is an experiential degree programme that focuses on transforming you into a hands-on, skills-driven, strategic data science manager in today’s data-driven economy.

Artificial intelligence (AI) and machine learning (ML) both serve similar functions. Regardless of industry, ML and AI have drastically altered the landscape and created new ways of viewing data. All are backed by standard statistical and mathematical principles.

This MSc programme in Data Science, Machine Learning, and Artificial Intelligence brings together the nuances of both disciplines to offer students exactly what is needed to understand the world of data, both in terms of tools and theory. Machine learning enables students' business decision-making and analytics.

Primary Outcomes:

1. Gain an understanding of data science, AI concepts, and MI algorithms with the application of each.
2. Develop critical thinking by taking up assignments that require problem solving, inference, and perception.
3. Understand business problems and weave an approach to solving them through learned principles.
4. Figure out a method to judiciously study and scan data to apply ML algorithms to reveal insights.
5. Be familiar with the tools and technologies used in the data science industry.

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