60 ECTS
35913
270h
Semester 3
Code MMUCA301-MMUCB301-MMUCC301
ECTS 5.00
Delivery mode On campus
Lecture Hours 30.00
Teaching Language English
Code MMUCA302-MMUCB302-MMUCC302
ECTS 5.00
Delivery mode On campus
Lecture Hours 30.00
Teaching Language English
Prerequisite
Foundations on corporate finance theory (Modigliani-Miller, trade-off theory, agency issues, asymmetric information and financial decisions).
Basics of corporate valuation and accounting (financial statements, valuation methods: DCFs, multiples, cost of capital).
Code MMUCC303
ECTS 5.00
Delivery mode On campus
Lecture Hours 30.00
Code MMMCA302-MMMCB305-MMMCC302
ECTS 4.00
Delivery mode E-learning
Lecture Hours 24.00
Teaching Language English
Pedagogical objectives
By the end of the course, students should be able to:
- write a basic Python program;
- use versioning control software;
- read in and manipulate structured data using dedicated libraries;
- create some basic models and algorithms in a structured and documented way;
- synthesize information and present the results in a written form.
Code MMMCC301
Delivery mode On campus
Lecture Hours 12.00
Teaching Language English
Pedagogical objectives
After this training, students should be able to:
- explain the main concepts of an ERP and discuss its opportunities and challenges
- describe how typical business processes are supported in SAP ERP
- understand integration between components
- navigate in the SAP Fiori user interface of SAP S/4HANA
- execute transactions for different business processes
- use Stories in SAP Analytics Cloud
- synthesize information and present the results in a written form
- work effectively in team
Prerequisite
Basic knowledge in financial and management accounting
Basic knowledge in information technology
Code MMUCA307 - MMUCB307- MMUCC307
ECTS 5.00
Delivery mode On campus
Lecture Hours 30.00
Code MMMCA302-MMMCB305-MMMCC302
ECTS 4.00
Delivery mode E-learning
Lecture Hours 24.00
Teaching Language English
Pedagogical objectives
By the end of the course, students should be able to:
- write a basic Python program;
- use versioning control software;
- read in and manipulate structured data using dedicated libraries;
- create some basic models and algorithms in a structured and documented way;
- synthesize information and present the results in a written form.
Code MMUCA304-MMUCB304-MMUCC304
ECTS 2.50
Delivery mode On campus
Lecture Hours 15.00
Teaching Language English
Pedagogical objectives
On completion of this course, students should be able to:
- Be familiar with the econometrics techniques used in financial analysis (e.g. event studies, differences- in-differences, time series analysis, panel data analysis)
- Develop an econometric model to test an economic hypothesis
- Implement such an econometric model using standard econometric software (e.g. identify the data, create variables, apply econometric techniques)
- Interpret the outcomes of empirical analyses
- Present the results of the empirical analysis in a professional manner.
Prerequisite
Intermediate knowledge in finance theory and in econometrics.
Code MMUCC306
ECTS 4.00
Delivery mode Blended
Lecture Hours 24.00
Teaching Language English
Pedagogical objectives
By the end of the course, students should be able to:
- articulate the mechanism behind the blockchain
- collect and analyse blockchain data
- assess applications of blockchain to financial services
- synthesise information and make focused presentation
- describe how peer-to-peer lending platforms work
- assess to what extent peer-to-peer lending complements traditional banking
Prerequisite
A basic understanding of the financial services industry. General knowledge of personal computer; Excel (intermediate); Python (beginner).
Semester 4
Code MMUCA400-MMUCB400-MMUCC400
ECTS 5.00
Delivery mode On campus
Lecture Hours 30.00
Teaching Language English
Code MMUCC402
ECTS 4.00
Delivery mode On campus
Lecture Hours 24.00
Teaching Language English
Prerequisite
Students should have followed a programming class, a statistics or econometrics course or its equivalent.
Students must have their own laptops with the following software:
R: https://www.r-project.org/about.html
Rstudio: https://www.rstudio.com/products/rstudio/download2/
Microsoft Machine Learning Server: https://docs.microsoft.com/en-us/machine-learning-server/install/machine-learning-server-install
Code MMUCC403
ECTS 4.00
Delivery mode On campus
Lecture Hours 24.00
Teaching Language English
Pedagogical objectives
By the end of this course, students should be able to:
- Describe the structure and master data in the financial components of SAP ERP
- Execute transactions in Financial Accounting and Management Accounting
- Explain some keys aspects in the configuration in Financial Accounting
- Execute planning functions in Management Accounting
- Describe SAP innovations in Finances
Prerequisite
- Basic knowledge in financial and management accounting
- Basic knowledge in SAP ERP
Code MMUCB404-MMUCC404
ECTS 4.00
Delivery mode On campus
Lecture Hours 24.00
Code MMMCB401-MMMCC401
Delivery mode On campus
Lecture Hours 12.00
Teaching Language English
Pedagogical objectives
At the end of the course, students should be able to:
- describe principles and characteristics of IFRS/IAS for consolidated financial statements
- evaluate differences between IFRS/IAS and GAAPs
- apply intricate IFRS/IAS requirements
- execute consolidation of simple financial statements
Prerequisite
A first course in financial accounting and consolidated financial statements.
Code MMMCB402-MMMCC402
Delivery mode On campus
Lecture Hours 12.00
Teaching Language English
Pedagogical objectives
At the end of the course students should be able to:
- explain the principles and regulatory framework of financial and sustainability audit
- describe the audit procedures
- design the articulation of the audit phases: discuss the business of the company, define the audit strategy, assess internal control, execute substantive procedures, and conclude
Prerequisite
A first course in financial reporting and consolidated statements.
Code MMUCA405-MMUCC405
ECTS 4.00
Delivery mode Blended
Lecture Hours 24.00
Teaching Language English
Pedagogical objectives
By the end of the course, students should be able to:
- leverage PyData ecosystem to program data science tasks efficiently
- perform data collection, exploration and preparation
- map practical problems to available ML approaches and methods
- implement an end-to-end ML pipeline and assess its performance
- apply ML to common financial use-cases
Prerequisite
Personal laptop with wifi, basic experience with any programming language, basic understanding of math, logic and algorithms.
Code MMUCA406-MMUCB406-MMUCC406
ECTS 15.00
Delivery mode On campus
Teaching Language English
Pedagogical objectives
At the end of the internship students should be able to:
- apply academic concepts in a practical situation in a professional environment
- expand content specific and technical skills
- reinforce the professional network
- respect and integrate the opinion of others
- synthesize information and make focused presentation
- apply ethical considerations to management decisions