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Degree
Bachelor of Science (BSc)

Duration
7 semesters

Tuition fee per semester
6.950 Euro

Tuition fee for semester abroad may differ

Language
EN

Start of programme
September

About the programme

Our Bachelor of Science in Computational Business Analytics is designed for those who seek a dynamic technology-focused business career. Being able to understand the manifold contexts of managerial decision-making and combining it with deep knowledge of data analysis techniques is an increasingly valuable skill set for a successful career in many industries. With the emergence of big data, companies see themselves confronted with highly complex decision-making problems that require experts that are able to speak fluently to both decision-makers as well as data scientists.

Business Analytics is concerned with the development and application of quantitative approaches to support managerial decision-making. Experts in this domain are familiar with different methods for data collection and acquisition, they are able to analyze data and build statistical models, and they can translate the outcomes of data analyses to actionable recommendations for managers. On top of this, they need to have a thorough understanding of the different areas of management, including accounting, finance, marketing, and operations.

Blog Post about Data Science

How is Business Analytics and Data Science used?
  • Image and speech recognition (e.g., Facebook’s photo tagging, Amazon Alexa)
  • Search engines (e.g., Google)
  • Recommendation management (e.g., Amazon, Netflix, Boooking.com)
  • Design of production and logistics services (e.g., Rewe home delivery, Intel’s chip factories)
  • Automated processes (e.g., credit card approval, sports betting)
  • Sales and demand forecasts (e.g., Zara, Roche)
This programme is the right thing for you if
  • you are interested in new and innovative technologies and their application in the business world
  • you have strong analytical skills and want to work on interesting and important problems
  • you are hands-on and like to work with computers
  • you are eager to discover the benefits and challenges of big data

Bachelor Day

Come and meet the team on our Bachelor Day! You’ll be provided with everything you need to know about admission requirements, financing your studies and current student experiences. The informative day will help you in deciding whether Frankfurt School is the right place for you and you may even get to know some of your future coursemates.

Next Bachelor Day

Date: April 25th, 2020 | Time: 10:00 a.m. - 4:00 p.m. | Location: FS Campus

Register Now!

Curriculum

Our Bachelor in Computational Business Analytics curriculum provides students with the skills required to succed in a career where data science meets the needs of contemporary business. Students will take core business and data science modules and learn how to combine their knowledge in the professional world.

Course content

Principles of Finance

After successful completion of the module, students will be able to:

-  Show the importance of finances for companies
- Analyse the investment and financing possibilities of companies
- Present the pricing of securities on the financial markets
- Explain portfolio and capital market theory and its practical relevance
- Examine the interaction of supply and demand on financial markets under different information scenarios

Financial Accounting

On successful completion of this module, students will have a thorough
comprehension of the basic and key concepts of bookkeeping, and a
good understanding of accounting rules guiding financial statements
preparation, i.e., they can:

  • Describe the objectives of financial reporting
  • Explain the flexibility inherent in accounting rules
  • Outline the concepts and techniques of financial statement preparation

Introduction to Data Science

This course provides an overview of different techniques for data analysis and the challenges associated with the usage of these methods. The students will also receive a thorough introduction into programming with Python and its related libraries, and understand different types of data.

Microeconomics and Decision Theory

On successful completion of this module, students are familiar with the basic concepts of decision theory and microeconomics, i. e. they can:

  • Answer the basic economic question on how the interplay between individual decisions drives market outcomes and social reality.
  • Outline the interrelation of decision theory and microeconomics
  • Describe how decision processes are structured
  • Emphasise the domain dependant relevance of different motives and preferences

Algorithms & Software Concepts

This module will expose students to different types of algorithms that are used to numerically solve problems frequently occurring in managerial as well as data analysis applications. Students will also acquire a deeper understanding of the structure of the underlying optimization problems, and thus be able to build computationally efficient models for data analysis.

Operations Management

This course is about how companies can design their operations to better match supply with demand and thereby gain a significant competitive advantage over its rivals. A better match of supply and demand can be achieved by using an adequate set of operations management tools, more specifically, by implementing rigorous quantitative models and well-understood qualitative operational strategies. This course introduces a broad range of operations management tools and aims at teaching the participants how and when to apply them in practical settings.

Data Collection & Games and Incentives

The first part of this course will expose students to different methods for data collection, and familiarize them with the strengths and biases of the different methods. Students will also learn how to assess the trustworthiness of data. The second part of the course will give students an introduction to game theory and the role of incentives for managerial decision-making.

Computational Statistics

This course teaches students contemporary regression-based techniques that are used for machine learning applications. Particular emphasis will be given to both supervised and unsupervised learning methods. The course will also expose students to the fundamentals of statistical decision theory and its importance for managerial decision-making.

Corporate Finance

Information to follow

Machine Learning

This module will build on the Computational Statistics course and discuss advanced machine learning techniques. Topics will cover the full range of supervised, unsupervised and reinforcement learning. Students will also understand the computational challenges arising during the implementation of advanced data science methods.

Principles of Management

The course introduces the concepts, tools, and principles of management
in today’s global business context. Our journey begins with an
introduction of what management is and a brief overview of management
history. We then explore the external and internal environment that
provide a context for how managers perform their jobs. We next examine
how managers make decisions as the decision making process is central
to how organizations operate. The rest of the course is organised around
the four functions of management, namely; planning, organising, leading,
and controlling.

Mathematics

This course will equip students with a basic understanding of essential concepts in the mathematical fields of calculus, algebra, numerical analysis, and optimization theory that are required for many managerial as well as data science and machine learning applications. It hence serves as the building block for all other courses in the program.

Science, Norms & Values

This module pursues two objectives. Firstly, it trains students’ analytical skills and ability for logically valid and sound reasoning. Secondly, it assesses the philosophical foundations and normative implications of business studies and economics. As such, this module is all about asking probing questions. Finding answers to these questions should, in turn, make us think better and, ideally, act better.

Statistics & Probability

On successful completion of this module, students will have a thorough comprehension of stichastic concepts, needed to treat statistical problems related to economic and financial issues, i.e. they can describe fundamental concepts from different fields of statistics and probability theory.

Data Bases & Data Management

This course will familiarize students with the basic concepts of data bases, ranging from the creation of data bases over data manipulation techniques to the extraction of relevant data. Students will also explore the challenges of working with different types of data.

Managerial Accounting

On successful completion of this module, you can take responsibility for designing and implementing managerial accounting concepts in organisations. You will be able to critically analyse the suitability of different managerial accounting approaches for the specific context of their organization. Moreover, you will learn to take into account interdependencies of accounting choices when implementing managerial accounting concepts.

Big Data: Ethical & Legal Implications

This module investigates ethical and legal questions that the emergence of ever larger datasets and advancements in (information) technology creates for management and society. Special focus will be given to issues related to privacy concerns, managerial responsibility as well as fairness considerations.

Macroeconomics

The module provides basic knowledge and methods for analysing the interdependence of goods, labour, money and capital markets in an economy. At the same time, it provides an insight into the major controversies between the most important economic schools and the consequences of these competing doctrines for the stabilisation policies of the government and the central bank.

Marketing

On successful completion of this module, students will have a thorough comprehension of Marketing, i.e. they can:

  • Understand the terminology, concepts and tools of modern marketing practice
  • Comprehend the consumer decision making process and the factors that affect it
  • Explain the marketing mix (product management, price management, sales management and communications management) and the importance of integrating these elements

Data Visualisation

This module bridges data science techniques with managerial decision-making. Students will learn how to effectively communicate the results of data analysis to decision-makers, and how to derive actionable recommendations for management. They will also learn how to derive meaningful insights even in the presence of severely biased data.

Study Model

Our Bachelor in Computational Business Analytics (BSc) is taught completely in English and studied full-time. This means you will have a normal 4 to 5-day a week schedule. Of course this can vary each semester, however usually you would have at least 1 day off during the week (lectures can take place between Monday and Saturday). It is also possible to take on a student working job on the side of our full-time model.

Learning experience

Our Bachelor in Computational Business Analytics (BSc) 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. 

Artificial Intelligence (AI) Lab

The AI Lab provides a space where new learning concepts can be developed, tested, and immediately implemented into the teaching programme. The AI Lab is equipped with four high end computers using the latest GPUs for AI acceleration. Students are also invited to attend our Hackthons and additional workshops. Find out more about our AI Lab here.

Hackathons

Our Hack@LAB hackathons allow students to solve problems chosen directly by a leading company. Students from a range of skill-sets come together and work on the problems using machine-learning techniques and algothrims.

Practical study approach

Next to your internship abroad, our studies combine theory and practice to broaden your knowledge through practical examples. Our professors work hand-in-hand with policy-makers and executives to offer tailor-made solutions to real-world questions. Research findings are employed in leading corporations, the finance sector, in politics and on development issues. Members of our faculty frequently follow and report on current issues in the media. Furthermore, managers from leading business companies frequently are invited by our teaching staff for guest lectures for our students.

During your studies, you will learn to analyse and calculate a companys‘ current situation by working on various case studies. If you wish, you may also write your Bachelor thesis in cooperation with a company.

Semester and internship abroad

The 5th semester abroad is an integral part of the Bachelor of Science. Firstly, you will go study at one of our over 100 partner universities. This will be an exciting and challenging experience. Every partner university offers different opportunities. The Frankfurt School International Office will support you with organising your semester abroad.

You will then also do an internship abroad which will allow you to gain practical experience around the world. The internship can be done in a different country from where your exchange university is located. Our Career Services will assist and support you during your search for an internship.

Entry requirements

When should I apply?

We strongly recommend you apply as early as possible, however no later than May 31st  if you would like to be guaranteed a spot in our Bachelor of Science programme. You are required to provide us with all necessary documents and successfully complete our application process.

Applications after May 31st will still be considered, however places will be assigned depending on availability and academic merit.

When applying to our Bachelor in Computational Business Analytics (BSc), you must be aware of all the documents required. Your place at Frankfurt School will not be confirmed until all the documents stated below have been delivered to us.

  1. A recognised secondary school diploma (German "Abitur" or equivalent)
    If you have not graduated yet, then you can apply by uploading your last two school reports
     
  2. Frankfurt School Assessment Centre or one of the following test scores: SAT, ACT, TestAS
     
  3. A letter of motivation 
     
  4. Your CV (resume)

Career prospects

On completion of the Bachelor in Computational Business Analytics (BSc) you will be qualified to connect the dots for companies. Business Analytics gains increasing importance in practice, and many global companies, including banks, consulting companies and large manufacturing and service firms, are seeking experts who understand the specific needs of managerial decision-making and can provide relevant (data-driven) solutions for genuine business transformations. 

Both the private sector as well as the public sector are constantly looking for ways to increase efficiency and effectiveness. Your skills as a Business Analyst are in such high demand that you may even receive job offers before you graduate. Job opportunities will include but are not limited to working as a Data Analyst, Data Visualisation Engineer, Data Scientist, Consultant, or Manager. Opportunities for you abound in all sectors that are experiencing digital transformation.

Career Services

Right from the start of your studies our Career Services team supports you as you search for exciting internships and your first job after graduation. They host two large in-house career fairs every year, regular workshops, visits by recruiters, and more.

Find out more

Living in Frankfurt

About the city

Frankfurt is not only the business hub of Europe but also the most international city in Germany. It accommodates 180 different nationalities and through its international airport and home to international companies it is a great place for you to live in. Located closely to the city center our campus is easy for you to reach.

More information about Frankfurt

Guaranteed Accommodation

We know that finding accommodation can be challenging, therefore at Frankfurt School we guarantee our first semester Bachelor of Science students a room for one year in our partnered accommodation (Urbanum) with a discount of 150€ a month, if the conditions mentioned below are met by 31 March 2020.

To be eligible for guaranteed accommodation you must:

  • Be starting your first semester in the Bachelor of Science programme at Frankfurt School in September 2020
  • Have signed your study contract and applied for accommodation by 31 March 2020
  • Be living alone (we don't provide guaranteed accommodation to couples or families).

You will be able to apply for accommodation once you been granted admission for our Bachelor in Computational Business Analytics (BSc) programme.

Non-guaranteed accommodation

You are still welcome to apply for our accommodation after 31 March 2020, however we can not guarantee you a room.

Further information about housing

Financing & Scholarships

Your degree is an investment towards your professional future. As a business school of international standing, we not only offer you academic excellence – we also offer you excellent career prospects.

As we can guarantee the quality of our teaching and research, we also expect the highest levels of commitment and motivation from our students.

We know that financing your studies can be an issue and must be thought about in detail. This is why we give our students the opportunity to receive financial aid or scholarships.

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