Solve real-world data science problems
The MSc in Applied Data Science is a response to the recent demand for business savvy data scientists with the collaborative skills to match. Our students will gain hands-on experience in solving real-world data science problems with our prominent industry partners, including Commerzbank and PwC, and will be equipped with the technical skills, business domain knowledge, and critical judgment to navigate the modern data ecosystem.
Highlights
- A combination of applied Machine Learning, Data Science and Business
- Problem Solving
- Ethical ramifications of the fourth wave of industrialisation
- Extended co-op company projects in cooperation with leading companies throughout third and fourth semesters
- Work part-time, study full-time with the 3-Day Model
- Participate in our hackathons
Short information
Degree: MSc
Major: Applied Data Science
Full-time / Part-time: Full-time
Duration: 4 semesters / 24 months
Start: September
ECTS Credits: 120
Price Total: 33000 €
Language: English
Application Deadline: June 31
Our students will master core data science and machine learning concepts, as well as the art and science of problem decomposition and solving. They will be able to identify business needs and wants, as well as problems, and propose relevant solutions using machine learning tools and by applying sophisticated statistical techniques. To do this, they will collect, transform and visualize data, create data models, as well as run predictions and simulations.
In a nutshell: The Frankfurt School of Finance & Management Master in Applied Data Science Programme provides the skills required to recognise and meet the data science wants of contemporary business, across-function and with an understanding of the connected ethical ramifications.
Semester 1
- Quantitative Fundamentals
- Algorithms & Data Structures
- Intro to Data Analytics in Business
- Computational Statistics & Probability
- The Language of Business
Semester 2
- Databases and Cloud Computing
- Machine Learning 1
- Machine Learning 2
- Guided Studies in Financial Management
- AI & Humanity: The Ethics of Data Science
Semester 3
- Strategy and Performance Management
- Deep Learning
- Natural Language Processing
- Cooperation Company Project
Semester 4
- Electives 1 & 2
- Study Abroad Option / Entrepreneurship Accelerator
- Thesis
Ideal Candidates
Our pre-experience Master programme is designed for students with an interest in developing cross-functional problem decomposition and solving skills by applying machine learning technology and data science, as well as business domain knowledge and critical judgment to navigate the modern data ecosystem.
Learning Experience
Frankfurt School applies a practical approach to your studies by preparing you for the realities of data science in the working world. We do this by strengthening your statistical, mathematical and computational skills, and through exposing you to every day working life as part of our cooperative company projects. Our guest lectures by external professionals with current knowledge of the market bring relevant and valuable cases to be solved in the classroom.
Career
On completion of the Master in Applied Data Science you will be qualified to connect the dots for businesses. These companies, including the Big Four, are seeking experts who understand specific wants and needs and can provide relevant solutions for genuine business transformations.
Job opportunities will include but not be limited to Data Analyst; Business Analyst; Data Visualisation Engineer, Internal Data Science Consultant and new roles in all sectors that are experiencing digital transformation.
We offer you the opportunity to work part-time throughout your studies. Proresult is a financial service consulting company who employs students with a background or interest in financial consulting and C1 level German skills. The cooperation guarantees a two-year part-time paid position at the company (3 days a week). In return, Proresult covers tuition fees in full.
If you are interested please apply within the online application.