The RSM MSc in Business Analytics & Management specialisation is one academic year’s duration. Core courses are compulsory and will be offered during the autumn semester (20 EC). Master electives are offered in Block 2 of the autumn semester (6 EC) and in the spring semester (10 EC). The Business Analytics Workshop (6 EC) takes starts in January. During the year, students work on a master thesis project (18 EC)..
Please note that certain electives may be very popular. Although we can place most students in the elective(s) of their choice, there are no guaranteed places.
View all core courses below:
The advanced statistics course is about acquiring a robust understanding of advanced statistical methods and techniques for business analytics, in terms of both foundation and application. In addition, the course provides training in advanced programming skills, specifically using the statistical software R.
In particular, the following topics will be covered:
Linear and general regression models
Least-squares estimation, maximum likelihood and bootstrapping
Statistical inference, estimation and hypothesis testing
Binary and multinomial choice modeling
Functional forms, nonlinear models
Models for panel data
Model selection, heteroskedasticity
Data is a key business resource. Web stores such as Amazon or Coolblue use customer data to dispatch purchased products and to make recommendations of new products; banking service providers such as ING or HSBC use data for processing cash and ATM transactions and for assessing a client’s credit worthiness; manufacturers such as BMW and Tesla use data to design and produce cars and to propel self-driving cars. Often, this data is spread within the organization through multiple information systems. In order for organizations to operate successfully, they need to be able to share data. Data management is the field dedicated to enabling the sharing of data such that it is available at the right time, place, user and quality. This course introduces data management topics such as database design, data preparation, manipulation, modeling, alongside with discussions on ethical frameworks that should guide the management of data and data privacy issues.
In addition, the course provides an introduction to blockchain, which is a new and atypical way of organizing data. This type of data solution arose in the wake of the global financial crisis of 2007-2009 with the introduction of Bitcoin, the first cryptocurrency. Ever since, there has been an enormous growth in different types of blockchain based business solutions, some of them meaningful, some of them not. We discuss the basic design, logic and economic incentives underlying the blockchain technology, and discuss real-life applications, hypes and scandals.
Course content is organized into seven modules covering the following topics:
- Introduction to Causal Inference—Overview of the course, motivating questions about causes and effects, and the challenges of measuring effects from data
- Potential Outcomes Model—A framework for measuring causal effects from observational data or experiments that begins with what you want to measure and works backward from that
- Graphical Models—Another framework for measuring causal effects from observational data or experiments that begins with what you are willing to assume about the world (and what you can measure) and works forward from that
- Randomized Experiments and Hypothesis Tests—Sampling from a population and random assignment to different treatments are powerful tools for measuring causal effects. Hypothesis tests provide a way to quantify how likely our results are due to these sources of randomness.
- Confounders and heterogeneity—The world is messy. Variables that are correlated with causes and effects can help or hinder our ability to measure causal effects for the entire population or for subsets of the population
- Matching and Regression Estimators—Introduction to typical methods for estimating causal effects
- Challenges to Causal Inference—If we send an email to a customer, they may or may not use that coupon on their next purchase. Here we discuss tools for inference when some people don’t do what we expect them to do.
Taught by Dr J. Roos.
The content is organized into 6 modules (the fourth one over 2 weeks), covering the following
- Introduction to quantitative decision making via Decision Trees ( Introduction to mathematical modelling, strengths and limitations, time structure of decisions, handling uncertainty). Introduction to Python.
- Linear Programming (Formulating and solving Linear Programs. The graphical method. Solving LP’s using Gurobi.)
- Sensitivity Analysis (Analyzing sensitivity of LP solutions with respect to data.)
- Integer Programming (Modeling discrete decisions. Formulating Integer programs, understanding why IP’s are harder to solve, modelling with binary variables)
- Incorporating Uncertainty in Linear Programming (2-stage stochastic programming, deterministic equivalent, non-anticipativity, connection with decision trees)
- Monte Carlo Simulation (Understanding the flexibility of simulation, creating and running simulation models in Python)
Through the course, we will apply the learned tools to areas such as operations and transportation logistics.
There will be five in-class lectures (1 x 2hr30m and 4 x 1hr15m) and five online workshops of 2hr45m each.
Taught by Dr A. Tsoukalas.
Machine learning is a key driver of the success of data-driven decision-making in business. It enables practitioners to learn from experience, as encoded in data, to understand business-relevant processes or to predict the future. It is an essential tool in the modern data scientist's toolbox.
This course provides a hands-on introduction to the concepts, principles and key algorithms for supervised and unsupervised machine learning. You will learn how these algorithms work and practice applying them to solve business problems. Attention will also be paid to principles, concepts and best practices which are required to apply these methods judiciously in practice, such as generalization, overfitting, resampling methods and evaluation metrics. The supervised and unsupervised machine learning algorithms covered will include decision trees, random forests, neural networks, cluster analysis and gradient boosting machines.
Machine Learning & Learning Algorithms is a core course in the MScBA Business Analytics & Management programme. It builds on knowledge obtained in the pre-modules and other core courses, with specific emphasis on statistics and programming. It provides knowledge and skills which will be leveraged to varying degrees by the elective courses.
Taught by Dr P. Schoonees.
The Business Analytics Workshop course involves completing a data analytics project for a company or organization. Together with the partner organization, teams of students formulate research questions, obtain and analyze data, and interpret and present their results.
Students are guided through the project by faculty supervisors. Guidance provided to students focuses on two domains: general skills and knowledge, and specific feedback on the project they conduct. Guidance related to general knowledge and skills focuses on project management, choice and application of research methods, and visual and oral presentation of results. In addition, students receive continuous feedback on their project progress from their peers as well as from supervisors.
Before the start of the course, students must indicate their preference for one of three tracks: (1) marketing, (2) supply chain management & business information management, or (3) accounting & finance. Based on these preferences, faculty supervisors form teams and allocate the teams to projects ahead of the course start.
The aim of ‘Your Future Career’ is to prepare RSM students at an early stage in their master's for their careers.
The online modules will help you make crucial steps towards the most suitable career step, whether an internship or a job.
To pass the course, you need to gain a minimum number of points within a few months. You can decide if you want to reflect on your interests and motivations, develop knowledge of the job market, receive peer feedback on application materials, learn to love networking, or attend an interactive alumni career panel or workshop.
See this page for more details.
All courses of this track are listed below:
In the last decades, the unprecedent growth of digital technologies has led to a rapid decline in the cost of storage, computation, and transmission of data. It deeply impacts firm internal business processes and interactions with other businesses, consumers, and policy makers. The aim of this course is to learn how digitization transforms production and supply chains, and leads to new products, services and business models, including platform businesses, such as Bol.com, Uber or Airbnb.
We will discuss changes brought in by digital technologies at the three levels: digitization, digitalization, and digital transformation. First, at the level of digitization we will see how the rise of new information & communication technologies affects the economy. At the level of digitalization, we will analyze how firms adopting these new technologies can benefit by making production processes and supply chains more effective. We will see how firms can transform their business models and discover new sources of value they can offer to their customers. We will particularly discuss digital platforms, focusing on their sources of value creation and the challenges they face.
Digitalization helps firms to use data generated by digitized processes as a new source of innovation and competitive advantage. At the level of digital transformation, we will focus on how companies can profit from innovating in the digital world and how data can support data-driven decision making.
In the second part of this course, we will look at specific challenges of digitalization for supply chain management and how they can be solved, based on practical examples. We will also learn how digital technologies revolutionize the customer journey through omnichannel distribution models.
Marketing is the interface between a firm and its environment. It is the managerial practices that ensure customer-oriented managerial actions, including product design, pricing, market communication and product distribution, generate value for “customers”. The basic tenet is that managers should be able to justify that intended value-creation actions lead to sufficient customer responses such that they surpass the costs of these actions. However, in practice, achieving such goal is challenging, because of the sheer number of uncontrollable factors that influence customer responses. To address these challenges, academics and practitioners have developed and adopted a selection of analytical tools in the form of “marketing models”, which are crystallized from disciplines such as economics, statistics and computer science.
This course focuses on 1) how to translate managerial problems into analytical problems, and 2) how to solve these analytical problems with marketing models. In paricular, the course covers important marketing problems, such as how to successfully design and diffuse a new product, how to price a product or service to gain short-term profits and long-term equity, and how to build and manage heterogeneous and dynamic customer portfolios. The course adopts a hands-on approach, where you are expected to work on cases with actual data to solve real managerial problems. Overall, the course will show you how to understand, predict and influence customers using marketing models.
Taught by Dr X. Chen.
This course lays the groundwork for financial modeling in Market-and Bank-Based Financial Markets. As such, the course is a building block for later the electives FinTech and Algorithms in control. We start by discussing sources of company financial information, how different financial statements are connected, and procedures for financial statements forecasting, accuracy assessments, and valuation. In particular, we discuss how data analytics can help in this process.
The results of such analyses are important for investors who use them in assessing the risk and return of investments in corporate credit and equity markets. In each of those two markets we derive a standard optimization representation both for individual investments as well as for portfolios. We link these representations to real-world applications such as platform (P2P) lending, asset management, robo-advising, and high-frequency trading.
All courses of this track are listed below:
The emergence of information and data technologies, together with the sophistication of tools in econometrics and machine learning, have led to a radical shift in the way marketing operations are run. The focus of companies has been shifted away from product-centric approaches and mass marketing campaigns to customer-centric campaigns tailored to the needs and wants of each individual customer. Such campaigns target a well-chosen subset of customers, at a well-chosen time, and with a well-chosen incentive. At their core, they require strong data analytics tools in order to be able to predict each customer’s behavior and derive optimal marketing interventions.
This elective will provide students with the necessary knowledge and skills to tackle these challenges. The course will focus as much on the managerial questions as well as on the use of methodologies to address these questions. The elective will be articulated around the core metric of Customer Lifetime Value (CLV). We will especially focus on customer-centric tactics firms can use to:
- Enhance customer acquisition (e.g. customer referral programs, seeding strategies)
- Boost customer spending (e.g. loyalty schemes, customer engagement)
- Prevent customer churn (e.g. proactive retention programs).
To address these challenges, we will use state-of-the-art machine learning methods, including boosting, uplift models, decision trees, etc. Finally, we use rely heavily on the notion of A/B testing and randomized control trials in order to optimize personalized interventions of firms.
Taught by Dr A. Lemmens.
The role of algorithms in organizations is twofold: on the one hand algorithms are used to control organizations, yet on the other hand algorithms themselves need to be controlled by organizations. This elective considers both perspectives. Firstly, to achieve their organizational goals, that is, to “be in control”, organizations use information from algorithms. To understand the use of algorithms for control purposes, this course will zoom in on control areas where information from algorithms is used such as personnel selection, performance management, and feedback and reporting. Secondly, to be in control, organizations also require information about algorithms. To understand how organizations aim to gain control over algorithms, this course will zoom in on risk areas of algorithms such as bias, opacity, and lack of accountability.
This elective aims to make you think thoroughly about the role of algorithms in organizations. During the course you will get hands-on experience with algorithms by gradually building-up your text analysis skills on real company data, culminating with a control motivated investigation of possible problems in text-based classifiers. The course also aims at teaching you helpful workflows that will stand you in good stead outside of this class (e.g., develop your business writing skills). This elective builds on the Data Management & Ethics core course and on the core elective Principles of Financial Modeling.
Taught by Dr I. Sandu.
Business analytics is becoming a key driver of competitive advantage. Only firms that can harness their data and develop strong analytic capabilities across all their business functions will be able to survive in fast-moving modern markets. In this course, students will learn how to use Python to manage and analyse large data sets, and present and communicate the results of their analyses in a manner that makes them actionable and understandable to business managers.
Taught by Dr P. Cornelius.
Recent years have witnessed dramatic changes in the ways businesses manage their supply chain operations, engendering a fundamental reliance on massive data from varied sources and advanced business analytics. New businesses have emerged with an explicit data-centric approach to supply chain operations, e.g. Amazon, Coolblue, Booking.com, while traditional suppliers (and other organizations) are heavily investing in transforming towards data-supported supply chain operations. Data about transactions and processes are central to forecasting product demand, to predict arrival times, to identify anomalies and structural changes, to monitor customer behavior or to estimate utilization rates. The analytics outcomes support operational, tactical, and strategic decision making throughout the supply chain: assortment planning, inventory management, workforce planning, procurement and production decisions, risk assessment, pricing, and the planning of logistics resources, routes or terminal capacity. Supply chain analytics is at the heart of the modern business.
This elective will introduce modern forecasting and machine learning methods to predict supply chain outcomes. Also, it will present methods to determine optimal prices, routes and inventory levels. All discussed methods and techniques will be embedded in typical supply chain topics.
Taught by Dr M. Tekin.
Consumers use various technologies in their everyday life, such as mobile applications, internet browsers, social networks, and wearables. In doing so, consumers leave a digital footprint - a stream of data that describes their online activities. Sometimes, they explicitly share content with other people (e.g. social networks, forums) or have direct communication with a company (e.g. online customer service). Data that consumers intentionally submit online is defined as active digital footprint. At the same time, consumers also leave a passive digital footprint: their search history, the news they read online, the location and time when they use a device. Both active and passive digital footprints can reveal consumer attitudes, interests, and preferences. This brings numerous opportunities and challenges for companies, consumers, and public policy makers.
This course is suitable for students with a solid understanding of fundamental programming principles who want to learn advanced scientific computing practices (e.g., collecting data using APIs, version control systems). As a core component of the course assessment, students will work through the steps of a data science research project (e.g., study design, data collection, data processing, data analysis). The lectures and workshops will cover data collection and data processing with R and RStudio. It is assumed that students already have an in-depth understanding of study design and data analysis, from previous courses in the BAM program. If you are unsure about the level of your R programming experience, please contact the lecturer before signing up for this class.
Taught by Dr A. Martinovici.
The financial sector has been increasingly disrupted by the use of technology. Moreover, recent regulations such as Mifid I&II and the EU PSD2 directive, have created an environment that further facilitates the use of technology, big data, and algorithms in financing applications. One can think about payment systems, Peer to Peer Lending, Crowdfunding, Crypto-currencies, Robo Advising, and High-Frequency Trading.
The course consists of two parts that run in parallel. In the first part, we discuss the FinTech business models and strategies, their value propositions, their impact on traditional players in the financial sector, and their impact on market outcomes.
In the second part of the course, we apply the knowledge gathered thus far in this course and the core courses by implementing a stylized version of one of these business models (an algorithmic/high-frequency trading operation) under the supervision of an instructor with ample real-life experience of doing so.
Note regarding taking courses if you are not an RSM master student: RSM does not offer the possibility for non-RSM students (master or otherwise) to take RSM MSc courses outside of official exchange partnerships or other inter-faculty agreements. If you are interested in learning more about corporate social responsibility, sustainability, or business ethics, please refer to our Open Programmes section.
For more information on all international opportunities offered at RSM, visit the website of our International Office.
Your Future Career
See this page for more details.
Business Analytics & Management is a new specialisation of our MScBA designed to fulfil the growing business demand for graduates with strategic business and management skills who can create business benefits using advanced analytics. RSM master graduates are individuals who all combine intellectual curiosity with practical skills geared towards creating positive change in business. In our most recent survey, 92.4 per cent of all RSM graduates find a job within six months of graduating – in many cases before they graduate. Students choosing this master programme may consider career paths as:
- Supply chain analyst
- Marketing analyst
- Data scientist
- Business analyst
- Financial modeller
- Financial analyst
- Customer journey specialist
- Omni-channel specialist
- Assortment and pricing specialist
Non-EEA nationals who have earned a diploma from a higher education institute in the Netherlands can apply for a special residence permit called the orientation year after completing their studies. The 'Orientation Year for Graduates Seeking Employment' is a residence permit aimed at retaining foreign talent for the Dutch labour market. During this orientation year you are free to work without a work permit. Participants who find a job during this period can change their orientation year into a residence permit for Highly Skilled Migrants under more favourable terms.
For the most up-to-date information please visit the website of the Nuffic.
MSc employment report
Vacancies for BA&M students
Studying at RSM
The RSM Experience
Education for life
Studying at RSM will be a life-changing experience. Your master degree will prepare you for a fulfilling professional life as a capable, self-assured individual. It will make you valuable to business and attractive to employers because it teaches you skills that make the most of your innovative mind. You will be challenged in and outside of the classroom, and you will gain an education based on the latest developments in business. Your master degree from RSM will include RSM’s promise of life-long learning, and membership of the more than 40,000-strong alumni network that is present in more than 110 countries which hosts activities and events all over the world.
Open intellectual culture
Your education at RSM is valuable. You will learn from academics who produce the highest quality research and the most innovative management thinking. In the classroom, sharing and questioning opinions is encouraged – yours and those of your fellow students, as well as the professors’. Many of RSM’s faculty members are young and passionate professors and researchers with outstanding academic credentials. Their work is published in top international management journals.
Professors’ doors are always open for students who have questions, projects or ideas. Depending on the study programme, students have different opportunities to tailor their programme. This can, for example, take the form of a minors course, an internship, an exchange at one of over 160 partner schools worldwide, elective choices, the participation in a consulting project with a company or public sector organisation, or a thesis project in their specific area of interest. RSM’s strong links with local and international businesses and organisations offer opportunities for practical projects and real-life collaborations.
Rotterdam, a future-oriented city
Living and studying in Rotterdam has never been better. Rotterdam is home to one of the largest and busiest ports in the world and many multinational companies have their headquarters here. The city is famous for its stunning modern architecture, such as the Centraal Station or its covered food market, the Markthal. At the same time, the city authorities are forward-thinking in improving its liveability. There’s no shortage of restaurants, museums and theatres, yet Rotterdam is still an extremely student-friendly city with plenty of affordable student housing, and a bustling nightlife that includes events organised by students associations.
Find out more about life in the city of Rotterdam.
Explore the campus
Life in the city
Coming from abroad
Fees & Scholarships
The combination of affordable tuition fees and living costs together with quality education and an excellent global reputation make a Masters degree at RSM a clever investment.
The 2023-2024 tuition fee for the MSc programmes is approximately €21,500 for non-EEA students. The Dutch government contributes towards this cost for students who hold a nationality from a country belonging to the European Economic Area(EEA). These students therefore only pay the statutory fee (€2,209 in 2022-2023, 2023/2024 is still tbd).
For EEA nationals who have already completed a master in the Netherlands (and obtained the diploma) the tuition fee for a 2nd master is approximately €12,600.
The MSc International Management - CEMS (18 months) is a longer programme, for which the tuition fee will have to be paid for the duration of the programme. The expected tuition fee for the 18-month MSc International Management - CEMS programme is approximately €32,250 for non-EEA students and was approximately €3,314 for EEA students in 2022/2023 (2023/2024 is still tbd).
Please note that all these tuition fee tariffs are subject to change.
The number of scholarships is limited and mainly merit based. If a scholarship covers only the tuition fees, be aware that you need to finance your own living expenses (rent, food and insurances) for the duration of your studies. RSM does not offer scholarships for the pre-master programme. We do however offer a maximum of 2 scholarships per academic year to RSM pre-master students enrolling in an MSc programme.
Rotterdam School of Management, Erasmus University (RSM) offers multiple scholarships to prospective students from non-EEA countries who are not entitled to pay the EEA tuition fee, provided their grades are considered ‘excellent’. RSM also offers one scholarship, the Erasmus Trustfonds Scholarship, to students from EEA countries.
Besides scholarships awarded by RSM, there are also scholarships awarded by the Dutch government or other organisations that are available if you meet certain criteria such as nationality, age, etc We have listed some of them below but we encourage you to use resources such as Grantfinder or the Scholarship Portal to find additional scholarships.
- G&D Europe Scholarship
- NN Future Matters Scholarship
- Russia: The Global Education Programme
- Contact the Ministry for Higher Education in your home country to see whether there are scholarship options.
- We have virtual information session covering all you need to know about scholarships and financial aid. Watch it here.
Master Application Handling fee
After having filled in all of the necessary application information on the Online Application Form (OLAF) and uploaded the required documents, applicants with a degree obtained outside the Netherlands will be asked to pay a non-refundable €100 handling fee. This fee can be paid online via the Erasmus Payment System which uses either iDEAL (for those with a Dutch bank account) or PayPal (which can be linked to any bank account or credit card worldwide). It is important that applicants complete the payment process as indicated, otherwise the system cannot register the payment.
The additional expenses in addition to tuition and general living costs vary per programme and may include:
- Study materials such as books, readers and business cases
- Costs involved in kick-off meetings
- Costs related to travel, international excursions and compulsory exchange semesters or internships abroad
For a reasonable standard of living in the Netherlands, you should have an income of approximately €1,000 per month or €12,000 per year (excluding the tuition fee). Here is an example of monthly expenditure:
- Furnished Accommodation, including gas and electricity €525
- Medical insurance €50
- Telephone €25
- Food €200
- Books, recreation, clothing, public transport, etc. €200
Total costs per month €1,000
Study and work - part-time jobs
Please ensure, prior to your arrival at RSM, that you have or will have sufficient funding available to finance your stay at RSM. Finding a part-time job, may be an option, but can not be guaranteed. You should therefore not rely on finding other ways to supplement your income during your studies. For additional information on obtaining a part-time job, visit the website of the Nuffic.
For EEA students there are no formal restrictions in finding work in the Netherlands, but students with a lack of Dutch language skills will find it difficult to secure employment. Non-EEA students are subject to labour regulations, which makes the likelihood of obtaining a work permit very small. We therefore ask students not to rely on this possibility. We do not encourage students to combine studies with the heavy workload from a part-time job.
Admission & Application
On this page we have listed the minimum admissions requirements. Please read the information carefully before moving to the application process. Also make sure to check out our extensive Frequently Asked Questions section.
The application for all programmes starting September 2022 are closed. The application for September 2023 will open 1 October.
Important immigration information for NON EU/EEA Full-time BScIBA and MSc students
Depending on your nationality, you might need an Entry Visa and / or Residence Permit for the Netherlands, issued by the Dutch Immigration and Naturalisation Service (IND). Students can only apply for an Entry Visa and / or Residence Permit through the RSM/ Erasmus University. Only with a valid Entry Visa and / or Residence Permit you are allowed to study at RSM/ Erasmus University.
Needless to say that RSM/ Erasmus University is not the institution that determines the requirements. The IND is the official governmental body that sets the rules and procedures.
Full-time BScIBA and MSc students who accepted their offer and hold a passport from an EU/EEA country do not need to apply for an Entry Visa and / or Residence Permit.
Full-time BScIBA and MSc students who accepted their conditional or unconditional offer and have a nationality and hold a passport of one of the following countries: Australia, Canada, United Kingdom, Japan, Monaco, New Zealand, South Korea, USA or Vatican State.
Full-time BScIBA and MSc students who accepted their conditional or unconditional offer, have a nationality and hold a passport of one of the countries mentioned in Group III and IV. This procedure also applies to students with a Surinamese nationality.
Note for Chinese students
Obtain a Nuffic Certificate : All Chinese students (with the exception of students from Hong Kong, Taiwan and students with a British Overseas Nationality) must register with EP-Nuffic for a ‘Nuffic Certificate’ before their immigration application can be started. The certificate is a document providing an assessment of your English language proficiency and of the authenticity of your educational degrees and diplomas. For more information, see the Nuffic website
Validity Entry Visa
An Entry Visa is valid for 90 days (counted from the day that you pick up your Entry Visa).
Validity Residence Permit
A Residence Permit is valid for the duration of your study plus three extra months. This means that you do not have to apply for an extension after one year.
I already have a Residence Permit for another EU/EEA Country
NON-EU/EEA students holding a (permanent or temporary) valid Residence Permit (e.g. for study purposes) for another EU/EEA Country no longer need to apply for an Entry Visa for the Netherlands. For these students, the procedure for a Residence Permit application applies. A copy of the EU/EEA-Residence Permit must be uploaded in your application. The Residence Permit must be valid at the time of the application, and still be valid when the student collects his/her Residence Permit in the Netherlands.
I already have a Residence Permit for the Netherlands
NON-EU/EEA students holding already a Residence Permit for the Netherlands (e.g. for study purposes, stay with partner or family, employment), need to apply for Switching Institutions, Change of Purpose or an Extension of your Residence Permit. Requests can be sent after being completely registered (onwards September 1st) to EUR International Office: email@example.com or 3 months prior to the expiration of your permit.
The Financial Requirements (determined by the IND)
Before your immigration application is sent to the IND, you are required to prove that you have sufficient financial means to cover your study (only for the first year of your study)
- the Tuition Fee (BSc IBA €9,600.-, MSc €18,700.-;
- the Immigration Fee (€ 192.-)
- the Costs of Living for 12 months (€11,400.-: €950.- for every month of your stay in the Netherlands)
Note: it is not possible to pay your tuition fee in instalments
Contact details for the immigration application
Your main point of contact for the immigration application at RSM/ Erasmus University is Ms. Joyce Maliepaard.
Once you have a conditional or unconditional offer you receive the ‘Immigration application process’ (from mid March on). The guidelines explains the procedure to successfully process your application. After having received the information you will be registered in student registration system ‘Osiris Zaak’ (‘Osiris Zaak’ opens in April).
After your registration in 'Osiris Zaak' your main point of contact is EUR Internatinonal Office (firstname.lastname@example.org). The immigration documents and invoice for the payment of the fees will be sent to you in 5 working days.
Deadline for MSc students
The deadline for uploading your immigration application documents and your proof of payment in 'Osiris Zaak' is: JUNE 15th. If this deadline is not feasible for you, please send an email to email@example.com
Deadline for BScIBA students
The deadline for uploading your immigration application documents and your proof of payment in 'Osiris Zaak' is: JUNE 15th. If this deadline is not feasible for you, please send an email to firstname.lastname@example.org
Release date: March 2021
Housing information for full-time RSM students coming to Rotterdam
Although a complete and useful overview of housing information for International Students can be found on the housing pages of the Erasmus University, the information below especially applies to RSM’s first year BScIBA and MSc students coming from abroad. Arranging your stay
As in many major European cities, the demand for reasonably priced housing in Rotterdam is very high. Therefore, make it your number one priority and start searching immediately after being conditionally or unconditionally admitted to our BScIBA or one of the MSc programmes. As campus housing is limited, you may have to look for a room on the private market or seek other alternatives.
The ‘Short Stay Accommodations’ of RSM is run by the housing corporation SSH Student Housing (SSH), specialized in letting furnished accommodation.
For our first year BScIBA and MSc students coming from abroad, we reserve a range of furnished accommodations. Students can only apply for ‘Short Stay Accommodations’ for the first 12 months of their study (it is not possible to rent a room for less than 12 months). After 12 months you have to find accommodation by yourself. The SSH Accommodation is not available for partners or family of the student.
Important: This message applies to all the students who have registered for the SSH housing for the 2022 academic year!
Please note that RSM has only 130 rooms to be divided among BSc and MSc students. A fair distribution will be made under the students. As SSH housing is limited, not every registration can be approved. Please be patient and waiting any approval. To increase your chances we strongly advice you to look for more housing possibilities here.
It is not possible to correspond about the result, neither by email nor by telephone
Available SSH housing/accommodation for BScIBA & MSc students
The SSH has four dorms you can choose from: one on-campus (Hatta Building) and three off-campus, only 15 minutes walking from the university (D'Blaauwe Molen, Overhoningen and Erasmus International House). All rooms/apartments are fully fitted and furnished (not self-contained) and located at Struisenburgdwarsstraat in the district of Kralingen, This district offers everything that a student needs: the Erasmus University, little shops and typical student pubs are around the corner. The centre of Rotterdam and the Kralingse Bos are just a stone’s throw away. In most cases you have communal cooking facilities and sanitary fitting. Accommodations can not be visited in advance, but descriptions of the different buildings are available on the SSH website. Please not that rental prices are re-indexed every year.
When am I eligible to register for a room at the SSH ?
You can register for a room once you have been conditionally or unconditionally admitted to the first year BScIBA programme or one of the MSc programmes.
When and how can I register for a room at the SSH?
- Tuesday 12 April 2022 at 12 PM: Start registration
- Tuesday 21 April 2022 at 12 PM: Start booking
IMPORTANT NOTE: The SSH start the registration for all Bachelor students (Erasmus University students) on April 12th, while the BScIBA students get the outcome onwards April 15th. This means that RSM start approving your registration at the earliest on Thursday 21 April. The date of registration for the MSc students has been changed:
Go to SHH* and fill in:
Your educational institution: Erasmus University Rotterdam (EUR)
Type of Resident: EUR Full Year Student (15 August 2022 - 31 July 2023)
When and how can I reserve a room at the SSH?
You can reserve a room and only see all the available rooms once your registration has been approved by the RSM. The approval proces for BScIBA students takes place onwards 19 April and for the MSc students on 12 May.
For BSc students: select and reserve a room
Log in to My SSH to reserve a room within 7 days*:
* If you have not selected a room within 7 days, your application will be set automatically to “not approved”. After this period you can no longer reserve accommodation via SSH (to give other students also a fair chance to apply for accommodation).
SSH will handle the whole process – from making a room reservation to payments. For more information about the Terms and Conditions, the Rental Guide and the FAQ’s, please visit the site www.sshxl.nl/en. Any questions can be addressed to: Rotterdam@sshxl.nl
Xior Building is a student building right next to the campus of the RSM/ Erasmus University. This 8th floor building upholds 280 studio apartments with all private bathroom and kitchen facilities.
Registration & Reservation opens on:
- Wednesday 11 May 2022 at 12.00 PM
Fixed rental period: 19 August 2022 – 7 August 2022
RSM is not in charge for the rental of these rooms and is only for students coming from abroad. Your registration will be checked by the Real Estate Services Department of the Erasmus University. All your questions can be addressed to email@example.com
The RSM/Erasmus University has a partnership with the companies SSH, XIOR, The Cohesion Cobana, Roomplaza and the Student Hotel. Additional information on the below mentioned housing providers, and many more, are listed on the Erasmus University Housing pages.
International Student Housing Rooms (ISHR)
Is a private initiative to manage shared living properties in The Netherlands. It was founded by former students of Erasmus University Rotterdam, who now work in the financial industry. ISHR is not an intermediary. It is a landlord-owned operating platform, developed based on lessons learned from a decade of interactions between international students and Dutch private landlords.The EUR has agreed on a partnership with ISHR and we have reserved around 40 flat share rooms exclusively for our first year International Bachelor or Master students.
Registration starts on:
Monday 2 May 2022 at 12 PM. Fixed rental period: 10 August 2022 - 31 July 2023
The Cohesion Cobana
Located in Katendrecht, Rotterdam. Katendrecht is a vibrant part of Rotterdam with a central location. The FIZZ Cobana has a variety of Friends apartments. This unique concept is a great way to share living space of your apartment, but still have all the privacy you want with your own bedroom. As a student of the Erasmus you will have a possibility to live with other Erasmus students in a Friends apartment. It’s a perfect blend of privacy and sociability, whenever you want it. The Erasmus University has reserved for its International students 40 rooms.
How to register? Please find here all the information.
Offers students the possibility to rent a flat with a group of like-minded people. They have 80 rooms for BSc and MSc students. You can apply as an existing group or use your find-a-flat mate tool to form your own. RoomPlaza has a safe booking process with a 100% guarantee of avoiding scams by fake accommodation providers. How to register? Please find here all the information.
The Student Hotel
A hotel located in Kralingen Rotterdam which offers fully furnished rooms with a private bathroom, shared or private kitchen, WiFi, flat screen TV. Included in the price is a bike, use of the gym, study rooms, lounges and game rooms, 24-hour reception, laundry room and a restaurant/bar
How to book a room? Please find here all the information.
Updated: 2 May 2022
Hostels in Rotterdam
Boat Hotel – a short stay apartment on a historical ship in the centre of Rotterdam.
King Kong Hostel - a very cool hostel that blends industrial design with 21st century contemporary art. It has a superb location in the beginning of Witte de Wittestraat which is in the heart of Rotterdam’s social scene and all the city’s best bars and restaurants are on your doorstep.
Hostel ROOM Rotterdam – located in Rotterdam’s historic Scheepvaartkwartier, near a beautiful little harbour. There are lots of good places for wining and dining in the area and close to the city’s main park.
Hostel Stayokay – this hostel is located in the city centre of Rotterdam in the striking cube houses. Next to Metro station “Blaak”.
As tenancy agreements are often only provided in Dutch (huurovereenkomst), we recommend you to view the additional information on this topic provided on the Erasmus University website. There you can also find information on Dutch housing terms, and other information on how to arrange your stay and other useful tips, for example on how not to get scammed.