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Computational Business Analytics students talking to each other Computational Business Analytics students talking to each other
Degree
Bachelor of Science (BSc)

Duration
7 semesters

Tuition fee per semester
7,050 Euro

Tuition fee for semester abroad may differ

Language
EN

Start of programme
September

Computational Business Analytics BSc will boost your career

Our Bachelor of Science in Computational Business Analytics is designed for students seeking a dynamic technology-focused business career. Understanding the manifold contexts of managerial decision-making and combining that with a 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 who can speak fluently to both decision-makers and 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 can analyse 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 are 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, Booking.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 one 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

Curriculum

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

Semester
1

Principles of Management

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
provides a context for how managers perform their jobs. We next examine
how managers make decisions, as the decision-making process is central
to how organisations operate. The rest of the course is organised around
the four functions of management, namely; planning, organising, leading,
and controlling.

Lecturers:

Dr. Stevo Pavicevic

Dr. Jiping Li

Financial Accounting

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

Lecturers:

Prof. Dr. Yuping Jia

Analytical Thinking & Critical Reasoning

Analytical Thinking & Critical Reasoning

Mathematics

Mathematics

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

Lecturers:

Dr. Pia Domschke

Introduction to Data Science

Introduction to Data Science

This course provides an introduction to data analysis using Microsoft Excel and Python/Pandas. The students receive a thorough introduction to programming with Python and its data science libraries; moreover, the students will also learn about the different programming paradigms underlying today's data science applications.

2

Principles of Finance

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

Lecturers:

Prof. Dr. Martin Faust

Microeconomics and Decision Making

Microeconomics and Decision Making

On successful completion of this module, students will be 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

Lecturers:

Prof. Dr. Heiko Karle

Statistics & Probability

Statistics & Probability

On successful completion of this module, students will have a thorough comprehension of stochastic 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.

Lecturers:

Dr. Pia Domschke

Algorithms & Software Concepts

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 optimisation problems, and thus be able to build computationally efficient models for data analysis.

Databases & Data Management

Databases & Data Management

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

3

Operations Management

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 their 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.

Lecturers:

Prof. Dr. Jürgen Strohhecker

Managerial Accounting

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 organisation. Moreover, you will learn to take into account the interdependencies of accounting choices when implementing managerial accounting concepts.

Lecturers:

Prof. Dr. Timo Vogelsang

Big Data: Ethical & Legal Implications

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 and, managerial responsibility as well as considerations of fairness.

Data Collection & Games and Incentives

Data Collection & Games and Incentives

The first part of this course will expose students to different methods for data collection and familiarise 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

Computational Statistics

In this course, students learn about state-of-the-art data analytics and machine learning methods, with an emphasis on supervised learning. The course will also expose students to the fundamentals of statistical decision theory and its importance in managerial decision-making.

4

Corporate Finance

Corporate Finance

On successful completion of this module, students will have a thorough understanding of the most recent advances in corporate finance. Examples can include M&A, private equity, venture capital, IPOs, debt financing, trends in financial technology, and risk management. Students will gain an in-depth understanding of the most recent trends in the industry and will be able to apply their knowledge in practical settings.

Lecturers:

Prof Dr. Yigitcan Karabulut

Prof. Dr. Larissa Schäfer

Macroeconomics

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.

Lecturers:

Prof. Dr. Benjamin Born

Marketing

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

Lecturers:

Dr. Britta Meinert

Dr. Tetyana Kosyakova

Machine Learning

Machine Learning

This module builds on the Computational Statistics course and covers fundamental machine learning techniques. Topics will cover a range of supervised and unsupervised learning algorithms. Students will understand how to employ the algorithms to solve a variety of practical problems ranging from financial time series forecasting to image processing.

Data Visualisation

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.

5

Semester Abroad & Internship

Semester & Internship Abroad

Use your semester abroad to study at an internationally renowned university in order to focus on a specific subject or to supplement your degree programme with new study contents. Doing an internship abroad will further allow you to gain important work experience in an international environment, improve your foreign language skills and come to know new countries.

6

Deep Learning / Elective 

Deep Learning / Elective 

This module offers you the further opportunity to tailor the content of your studies to fit your interests. Choosing from a wide array of business and economics modules, you can pick the subject that interests you most.

Data Science Module / Elective

Data Science Module / Elective

This module offers you the further opportunity to tailor the content of your studies to fit your interests. Choosing from a wide array of business and economics modules, you can pick the subject that interests you most.

Concentration

Concentration

The three interconnected concentration modules enable you to deepen your knowledge of a business or economics subject of your choice: Choosing from concentrations such as 'Banking & Finance', 'Innovation Management', 'Marketing' or ' Information Systems Engineering', select the one in which you want to expand your expertise.

Concentration

Concentration

The three interconnected concentration modules enable you to deepen your knowledge of a business or economics subject of your choice: Choosing from concentrations such as 'Banking & Finance', 'Innovation Management', 'Marketing' or ' Information Systems Engineering', select the one in which you want to expand your expertise.

Concentration

Concentration

The three interconnected concentration modules enable you to deepen your knowledge of a business or economics subject of your choice: Choosing from concentrations such as 'Banking & Finance', 'Innovation Management', 'Marketing' or ' Information Systems Engineering', select the one in which you want to expand your expertise.

7

Data Science Module / Elective

Data Science Module / Elective

This module offers you the further opportunity to tailor the content of your studies to fit your interests. Choosing from a wide array of business and economics modules, you can pick the subject that interests you most.

Elective

Elective

This module offers you the further opportunity to tailor the content of your studies to fit your interests. Choosing from a wide array of business and economics modules, you can pick the subject that interests you most.

Thesis Preparation Module

Thesis Preparation Module

This module prepares you for writing your bachelor’s thesis by discussing in detail how to phrase your research question and choose appropriate research approaches. We also review the formal and material requirements to which your bachelor’s thesis will be subjected.

Thesis

Thesis

You will complete your Bachelor of Science degree by writing a bachelor’s thesis, under our supervision, on a philosophical, business or economic research topic of your choice.

Thesis

Thesis

You will complete your Bachelor of Science degree by writing a bachelor’s thesis, under our supervision, on a philosophical, business or economic research topic of your choice.

Study Model

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

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Bachelor Day (Open Day)

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Next Online Bachelor Day: 12. February 2022

Join us to learn more about our Bachelor Programmes. Attend trial lectures, take part in a virtual campus tour and take the opportunity to get to know professors and students. We look forward to welcoming you online!

Register here!

Would you like to catch up on our last Bachelor Day from 27 November 2021? Here you have the opportunity to watch all presentations as well as various other videos.

 

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 by 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 Hackathons 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 algorithms.

CBA Practitioner Series

CBA programme organizes practitioner talk series where experts from the industries and academia share their knowledge on different topics related to data and business and how various industries they come from are being affected by data science.

The talk series serves as a communication tool with the goal to help young growing minds at Frankfurt School understand better the world of data science and its enormous application in many business environments. It is also a learning platform benefiting anyone interested in this field, but first and foremost helping our student groups to sharpen the focus on specific future jobs they will pursue and help them centre their attention on the specific passion that will lead them throughout their programme journey. Furthermore, as we grow our practitioner talk series, it will become a place of local and international data and computational science ecosystem able to provide networking and scientific exchanges for both businesses and individuals.

Our audience next to CBA Bachelor students includes Master students of Data Science programmes, FS Data Science initiative, faculty members of different departments and experts from the outside interested in our talks and speakers.

We are happy to welcome companies and professional individuals coming from the industries or academia to share their stories with us.

For any inquiries, feel free to contact z.zujic@fs.de

Our speakers from Spring Practitioner Series 2021
  • Dr. Heike Dengler - UBS Frankfurt - CFA Head Market Conformity Check - Machine Learning Applications in Financial Services.
  • Vahe Andonians - Lecturer and Practitioner, Partner alongside Moody's Analytics.
  • Dr. Ryuta Yoshimatsu & Inna Grijnevitch - D ONE Zürich
  • Dr. Yao Yang - Data Data Scientist - Infineon Technologies Münich
  • Dr. Sergio Solorzano - Senior Scientist/Software Engineer - EXEON Smart Cyber Security
  • John C. Lokman -  Communication and information specialist

Our speakers for the Fall Practitioner Series 2021, will be announced soon.

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, 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 are frequently invited by our teaching staff for guest lectures for our students.

During your studies, you will learn to analyse and calculate a company's current situation by working on various case studies. If you wish, you may also write your bachelor's 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 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.

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Student in Dubai

Entry requirements

We strongly recommend you apply as early as possible, however no later than June 30th 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 30 June will still be considered, however, places will be assigned depending on availability and academic merit.

You must fulfill the following requirements before the start of your studies:

  1. Complete a Secondary School Diploma* (e.g. German Abitur, Fachhochschulreife, IB, EB, or equivalent) - If you have not graduated yet, then you can apply by uploading your last two school report cards
     
  2. Successfully complete our Online Assessment Centre, which consists of:
  • Maths test
  • Cognitive tests
  • English test
  • Interview

Alternatively, you can provide us with one of the following test results in your online application: SAT, ACT, or TestAS plus a standardised English test (TOEFL, IELTS, Cambridge, or Pearson). In this case, you will also be required to take part in an online or telephone interview.

*If your secondary school leaving certificate does not meet the requirements for direct entry into German university set forth by the Ministry of Education, you have the opportunity to apply to our Pre-University Foundation Programme. Upon successful completion of the foundation course, you will be eligible to pursue your bachelor’s degree at Frankfurt School. If you would like to know more about the Foundation Progamme, you are welcome to take part in one of our information sessions.

Career possibilities

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 and 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 a digital transformation.

Excellent Career Prospects

Frankfurt School has an exceptional reputation and our Bachelor programmes open many doors and offer excellent career prospects for students. From day one, students are continously individually supported when it comes to their career, by our Career Services department. Exclusive events allow students to build their professional network. Furthermore, our Career Services provides students with access to our FS Mentoring Programme, various career-related workshops, and our FS Job portal throughout their studies. Frankfurt School ensures all students have the opportunity to already gain work experience at top companies during their studies and are prepared for a successful career upon graduation.

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 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. Since 2020 we offer a Data Science Diversity Scholarship, which applicants for the BSc in Computational Business Analytics might find particularly interesting.