Financial Engineering (MSc, Executive) at HECTOR School
Karlsruhe Institute of Technology KIT · Karlsruhe, Germany
- Level
- Master's
- Award
- Master of Science
- Language
- English
- Duration
- 4 semesters
- Study mode
- part-time (study alongside work)
- Campus
- Karlsruhe
- Apply by
- This programme has no deadline.
- Starts
- Winter semester
- Tuition
- €18,000
Entry requirements and how to apply
- Entry requirements
- University qualification: Applicants must submit proof of one of the following first academic degrees: Bachelor's, Master's, Diploma (German "Diplom"), etc. (university, university of applied sciences, cooperative state university), in a relevant subject such as engineering, natural sciences, information science, or economics. Other degrees may be accepted in exceptional cases. Professional experience: Depending on the level of the first degree (210 or 180 ECTS points) A minimum of one or two years of practical experience in the specific field of the course is required. Three years of work experience are recommended. References are required as evidence. For further details, please see: HECTOR School – Admission Requirements
- English language requirement
- C1 required, proof via placement test/interview
- German language requirement
- No minimum language level required
- Application period
- This programme has no deadline listed.
- Apply through
- Please check this website .
About this programme
We see modern Financial Engineering as the science of data-driven decision-making in business environments. Building more accurate models reduces uncertainty around future events and paves the way to better decision-making. Learning from data and using classical statistical concepts and novel concepts from machine learning help businesses across industries and geography solve predictive data analytics and valuation problems . Today’s predictive learning schemes perform tasks that were previously only solvable by a limited group of experts. Advances in predictive analytics and learning will affect all business models and industries. Financial tasks in particular will be transformed at an astonishingly fast pace. Vast amounts of data, paired with the individual's and institution's desire to plan ahead to meet future obligations and investments, make financial decision-making in its broadest sense an especially appealing application of predictive analytics and learning schemes. Our Master’s programme in Financial Engineering with a special focus on Data Science, Artificial Intelligence (Machine Learning) and Predictive Analytics prepares decision-makers to model and understand data across a variety of business fields and problems. The first two engineering modules teach fundamentals of finance, financial economics, data science and Python and pair these with novel developments in the field of digital business models, allowing our students to grasp the status quo and business opp
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