Our world and businesses in particular face disruptive change due to exponential growth of both the amount of data which can be captured from a wide range of data-sources and the computational capabilities to process the data. Future experts and managers will need to understand how to leverage Data Analytics and Decision Science to create value from data - this is what you will learn in this Master Program.
This exciting new master course is designed at the intersection of the fields of Data Analytics and Decision Science (Operations Research) and graduates will learn how to combine machine learning and deep learning techniques with mathematical optimization approaches, heuristic algorithms and simulation techniques to create value in specific application areas. RWTH Aachen is ranked number one in the field of Statistics & Operational Research in Germany by the QS World University Ranking 2017.
Data is becoming the new "oil", the raw material from which value is created as businesses become predictive enterprises and digitize their value chain. Each industry sector and application area will benefit from deriving optimal business decisions using data-driven techniques. Operational decisions are supported or even automated using state-of-the-art machine learning models combined with optimization techniques.
Become tomorrow’s technological expert by enrolling in our Master Program which combines the fields of Data Analytics and Decision Science. Learn how to develop state-of-the-art predictive models and how to make decisions that optimize business objectives.
YOUR PROFESSIONAL DEVELOPMENT AND CAREER PROSPECTS
The M.Sc. in Data Analytics and Decision Science (DDS) has been carefully designed to equip ambitious professionals with a STEM background with a distinct set of skills needed to succeed in a digitized and globalized economy.
Data-driven decisions become mission-critical in one vertical after the next. Many professions will face disruptive change, job descriptions will change significantly as data- and algorithm-driven decisions are at the core of creating value for businesses and new jobs will emerge. Tasks currently performed manually or supported by simple approaches will require specialized knowledge in Data Analytics and Decision Science, machine learning and optimization techniques in the future.
The M.Sc. degree granted by RWTH Aachen University in Germany will also enable you to pursue an academic career and continue studying towards a PhD in fields such as data analytics, machine learning & artificial intelligence, operations research and engineering.
Whichever way you want to follow after graduation: Our dedicated team of experts in the career and entrepreneurship centers will accompany you on that journey and help you decide how to best realize your ambitions, be it an exciting new job or starting your own business. We seek to place our graduates in global technology blue chips, hidden technology champions, leading technology consultancies and fast-growing technology ventures. The Entrepreneurship Center at RWTH Aachen University also has a long track record of supporting innovative startups by our graduates – between 70 to 100 every year.
The following list gives an idea of the possible data scientist jobs for the successful student of the Master Program, combining data analytics and operations research.
- Retail & Value Chain Management
- Industry & Production
- Transportation & Mobility
- Energy & Climate
Further application areas can be found in:
- Marketing (e.g. ad placement, SEO optimization, marketing campaign optimization, etc.)
- Healthcare (e.g. personalized medicine, automated diagnostics, etc.)
- Finance & Insurance (e.g. predictive underwriting, fraud detection, tariff optimisation, etc.)
- Politics & public sector
- Sustainability & Smart Living
In fact, it is hard to come up with an industry or service that is not directly or indirectly impacted by data and algorithms driven decision making. As the need for decisions changes (more flexible, real-time, under uncertain and ever-changing environments), a decision-making process rooted in mathematical optimization is unavoidable. Only predictive analytics (e.g. machine learning) can harness the potential of historic and present data; only prescriptive analytics (mathematical optimization and operations research) can capture the full range of options the decision maker faces.
YOUR ASPIRATIONS & PREREQUISITES
This program is ideal for you if you want to develop as a professional and transform your career.
Apply now if:
- You have a STEM (Science, Technology, Engineering and Mathematics) background, at least one year of full-time work experience and want to deepen your knowledge in machine learning, artificial intelligence, operations research techniques (mathematical optimization, heuristic algorithms and simulation), and data-driven decision making.
- You are passionate about engineering and technology and want to enhance your skills to face tomorrow’s challenges in creating value from data using algorithms.
- You want to learn how to leverage machine learning, artificial intelligence, operations research, and data-driven decision making into profitable and sustainable business models that allow you to lead the technological transformation in your industry rather than just following it.
- You have a good knowledge and working experience with at least one high-level programming language (e.g. Python, Java, C/C++), as well as some experience in developing software or contributing to a software project.
Future Data Analytics and Decision Science experts will need to bring together expertise from a wide range of fields:
- Machine learning, deep learning, and artificial intelligence
- Mathematical optimization, heuristic algorithms and simulation techniques
- Understanding, handling and enriching data
- Industry-specific knowledge (e.g. manufacturing & production, logistics & supply chain management, retail, engineering, energy & climate and others)
The M.Sc. Data Analytics and Decision Science (DDS) offers a comprehensive program of core courses in machine learning, mathematical and heuristic optimization and data-driven decision making. These courses are accompanied by a wide range of elective courses offering deep-dives into specific application areas. Our courses combine demanding and cutting-edge research with practical projects and challenges. We continuously review and expand the set of electives to cover the latest trends and stay abreast of technological change.
The two-year full-time program consists of seven key building blocks, some of which can be customized to meet your individual needs and interests. You may also enrol in a German language course at no extra cost.
DDS Essentials (10 CP to be completed in semester 1) The “DDS Essentials” consist of two courses that cover and refresh relevant essentials in mathematics, statistics, algorithms and data structures. These modules lay the foundation to participate successfully in the core courses in Data Analytics and Decision Science, as well as in some of the application areas and specializations.
Data Analytics (10 CP to be completed in semester 1 and 2) The block “Data Analytics” consists of three modules. The module “Predictive Modeling” covers the fundamentals in data handling and data quality issues, predictive modeling and validation of business- and use- cases, as well as evaluation of predictions. The course “Machine Learning” will focus on the fundamentals and cutting edge developments in machine and deep learning. The third module is a practical exercise that complements the two lectures.
Decision Science (15 CP to be completed in semester 1 and 2) This block consists of three modules: The module “Optimization Models” introduces the concepts behind building state-of-the art decision models that are able to capture the combinatorial explosion of options, including networks and linear and integer programs. The module “Design and Analysis of Algorithms” focuses on modern methods to solve these optimization models. The course covers algorithms not only for deterministic problems but also techniques from robust optimization and algorithmic game theory, which allow to handle uncertainty in the decision making process. The module “Heuristic Optimization” covers the fundamentals of metaheuristics and the challenges encountered when designing high-performance heuristics for complex planning tasks in different domains.
Analytics Project (10 credit points to be completed in semester 2)
The Analytics Project is a practical exercise that complements the lectures from the Decision Science and Data Analytics blocks. Teams of 3 - 6 students work together on a practically motivated analytics project and go through almost the entire analytics process using machine learning and optimization techniques: formalization of the problem, modeling, understanding, gathering, and cleaning of the data, algorithm selection and development, implementation, computational solution, visualization and interpretation, and documentation of results. You learn how to present your results to both a practice-oriented and a scientific audience.
Management and Soft Skills Electives (10 CP to be completed in semester 2) Choose two of the following elective courses to deepen your managerial competences:
- Engineering, Culture & Society
- Digital Work
- Strategic Technology Management
- Managing the Innovation Process
- B2B Marketing
- Service and Technology Marketing
- Start-Up and Growth Management
- Entrepreneurial Marketing and Finance
Technology Electives (5 credit points to be completed in semester 2) You choose one of three possible elective courses:
- Advanced Machine Learning
- Principles of Data Mining
- Industrial Logistics
Internship or Study Abroad (15 CP to be completed in semester 3) Apply your skills in an industry work placement at global enterprises such as Deutsche Post DHL, PTV Group and others, or deepen your knowledge by studying at an international university, or participating in summer schools or online courses.
Application areas (15 CP to be completed in semester 3) Gain detailed insights in the following domains:
- Digital Operations and Supply Chain Management
- Optimization of Logistics Systems
- Economic Modeling of Energy & Climate Systems
Master Thesis (30 CP to be completed in semester 4) By writing a master thesis at the end of the program you demonstrate your ability to solve a methodological or analytic challenge using the knowledge acquired during the program and the methods of scientific research.
German Language Course (one course to be completed in semesters 1 or 2) Learning another language is an important part of a successful career. Becoming proficient in German is also an essential precondition for succeeding on the German job market, both for an internship during your studies or a permanent position thereafter. As part of the program, we offer the option to complete an intensive German language course to broaden your cultural understanding and enhance your career options. You may be able to enrol in further language courses in semester 3 and 4 at your own convenience. The Student Counsellor will help you get in touch with the relevant contacts.
Students enrolled in this program will learn fundamental and leading-edge advances in machine learning, artificial intelligence, operations research and decision science. The courses are taught by world-leading experts in their respective fields. Elective modules allow the student to specialize in a variety of fields such as production or logistics to gain a deep understanding of specific industries.
The RWTH Business School is located on the new Campus of the RWTH Aachen University. The Business School and its parent organization, the School of Business and Economics at the University are among the less than 5% of business schools worldwide that are AACSB accredited. RWTH Aachen University is one of the global leaders in science and technology and has an excellent reputation in the scientific community and cutting-edge companies alike. The university is listed at position 29 of the Times Higher Education ranking for engineering and technology and at position 33 in the QS ranking. Crucially, RWTH Aachen is ranked at position 27 worldwide by “employer ranking” and position 12 in Europe in the field of Operations Research and Statistics in the QS university ranking.
OUR TEACHING APPROACH
- Student-centered learning: All courses are based on a participant-centered approach that emphasizes interaction between instructors and participants through case discussions, group presentations, debates, or lab sessions.
- Interdisciplinary mindset: Most courses focus on the intersection between technology and decision making, helping you tackle real-world challenges from multiple perspectives and providing you with a truly interdisciplinary mindset.
- Hands-on experience: In most courses, you have the opportunity to work on real-world challenges, enabling you to apply the knowledge gleaned in class and gain hands-on experience.
- Intercultural teams: As working in multicultural teams is a given in today’s world, most courses feature group projects where you can solve managerial and technological challenges in culturally diverse teams.
The M.Sc. Data Analytics and Decision Science (DDS) is delivered by the RWTH Business School and University as well as leading partners in academia and industry around the world. Choose between an exchange with one of the leading universities or gain hands-on work experience at one of our cutting-edge industrial partners.
Application deadline for Non-European applicants: March 1 of each year
Application deadline for European applicants: July 15 of each year
To apply for the M.Sc. DDS, you need to prove different academic and English language requirements.
- 125 credit points in mathematics and/or natural sciences (e.g. physics, chemistry, computer science or similar)
- 15 credit points in the fields of higher mathematics or statistics, database and information systems, programming, algorithms and data structures, complexity theory, quantitative methods/operations research
- Collect all documents in pdf format from our online checklist: https://www.business-school.rwth-aachen.de/en/application-process/
- Create an online application account using our online application portal: https://online.rwth-aachen.de/RWTHonline/ee/ui/ca2/app/desktop/#/login?$ctx=lang=en;rbacId=
The application portal opens in December and will remain open until 1st of March every year for applicants from outside Europe and until 15th of July for European applicants.
Follow our detailed step-by-step instruction or the points below.
Unfortunately, some options haven't fully be translated into English yet, please follow the steps below:
- You will need to create and activate an account for the application portal first.
- The course M.Sc. DDS will start in the Wintersemester
- Type of studies: Master program
- Intended degree: Master 1 Fach
- Entrance semester: 1 - manual admission
- Form of studies: further training studies
- Update your personal data. Fields surrounded by a yellow line are mandatory (Place and country of birth, first nationality). The system currently only supports male and female as gender, we apologize for any inconvenience caused.
- Update your correspondence address
- Update your permanent home address (unless identical with the correspondence address)
- Higher education entrance qualification: Details about your high school degree certificate and awarding school. Please select where you have obtained your degree (probably: I have obtained a foreign higher education entrance qualification) and type of school (general qualification - school abroad). Then provide all further details requested.
- Add an academic background or degree program. Note that you will be asked to enter your first major subject. Please note that unfortunately most of the list is still in German. Also, you are asked to indicate when you have studied. Unfortunately the system only knows about German semester times. If your university works on a different schedule. please use the closest approximation. The Wintersemester typically starts in October and ends in February, the Sommersemester typically starts around March/April and ends in June/July. Please contact us if you have any questions.
- Follow the online application process further and upload the required documents. Complete the online application through "send".
- Preview the application and check that everything is correct.
- The current status of your application can be monitored through the online application portal. If you are admitted, we will send the admission confirmation along with the contract by mail.
Checklist with required documents
- Your relationship with the author,
- Your academic/professional history,
- Your qualities/achievements/ambitions in your respective field,
- Your personal traits and goals,
- The author’s signature,
- The institution’s/company’s letterhead (if possible), and
- A stamp of the issuing institution/company (if possible).
- Complete address and contact details of the company,
- Date of joining and, if applicable, resignation date,
- Weekly hours,
- Job position, and
- Short description of tasks and responsibilities.
- Internet-based TOEFL with a minimum of 90 pts,
- IELTS (Academic) test with a minimum overall band, 5 pts.,
- Cambridge Test – Certificate in Advanced English (CAE),
- First Certificate in English (FCE), completed with a B, and
- Placement-Test of RWTH Aachen University's language centre (B2).
- For German applicants: Ein Zeugnis, das englische Sprachkenntnisse auf dem Niveau B2 des "Gemeinsamen europäischen Referenzrahmens (GeR)" ausweist. Dieser Nachweis wird z.B. durch die Vorlage eines deutschen Abiturzeugnisses erbracht, aus dem ersichtlich ist, dass Englisch bis zum Ende der Qualifikationsphase 1 (Jahrgangsstufe 11 bei G8-Abitur, sonst Jahrgangsstufe 12) durchgängig belegt und mit mindestens ausreichenden Leistungen abgeschlossen wurde.
- Title: Data Analytics and Decision Science (DDS)
- Degree: Master of Science (M.Sc.)
- Focus: Machine Learning, Artificial Intelligence, Operations Research, Decision Making
- Duration: 4 semesters full-time, including 1 semester Master thesis
- Target Group: Young professionals with a STEM (science, technology, engineering and mathematics) background
- Credit Points: 120 ECTS
- Tuition Fees: 30.000 € (+ social contribution fee at RWTH Aachen approx. 280€ per semester). Please consider applying for a scholarship.
- Contact: email@example.com
About the School
RWTH Business School’s leitmotif “The Technological Edge” stands for unique graduate and executive education made in Germany, and for outstanding programs at the intersection of management and technol ... Read More