Bridge courses are intensive courses taken before the start of a degree programme. Participation is voluntary and no credit points are awarded. Bridge courses are designed to refresh knowledge already acquired and to fill any minor gaps in knowledge.
Below you will find the bridge courses currently planned for the period from 7 to 18 September 2026. Please note that the programme is subject to change at short notice.
You can join the bridging course without prior registration simply by clicking on the link to the WebEx video portal for the relevant lecturer:
Malte Weber: https://hsrw.webex.com/meet/malte.weber1.
Sabine Lauderbach: https://hsrw.webex.com/meet/sabine.lauderbach
WebEx can be accessed via your browser. You can also use WebEx on your mobile phone. You may need to download and install the software, so please allow a few minutes for this. Please ensure you have a working microphone and, if possible, a camera.
If you have any general questions about the bridging courses, please contact Ms Daniela Menzel. Email: daniela.menzel@hochschule-rhein-waal.de
Bridge courses from 7–12 September 2026 (Mon–Fri)
| Time | Title | Language | Lecturer |
|---|---|---|---|
| Provisionally Mon–Fri 08:30–11:30 online | Mathematics, lecture | English | M. Weber |
| Provisionally Mon–Fri 12.30–15.30 online | Mathematics, lecture | German | M. Weber |
Bridge courses from 14–18 September 2026 (Mon–Fri)
| Time | Title | Language | Lecturer |
|---|---|---|---|
| Provisionally Mon–Fri 08:30–10:30 online | Mathematics, Tutorial | German | M. Weber |
| Provisionally Mon–Fri 10.30–12.30 online | Mathematics, Exercise | English | M. Weber |
| Provisionally Mon–Fri 10.30–13.30 online | Statistics | German | S. Lauderbach |
| Expected to be available Mon–Fri 14.30–17.30 online | Statistics | English | S. Lauderbach |
Topics covered in the individual courses:
Mathematics (German)
- Logic and Sets
- Elementary methods of proof
- Number systems
- Equations and inequalities
- Mappings/Functions
- Sequences
- Differentiability
- Vector spaces and vectors
Mathematics (English)
- Logic and Sets
- Elementary Proof Techniques
- Number systems
- Equations and Inequalities
- Mappings / Functions
- Sequences
- Differentiability
- Vector Spaces and Vectors
Statistics (German)
- Part I: Descriptive statistics, measures of central tendency and dispersion: mean, standard deviation, outliers, box plot and scatter plot, normal distribution, skewness, kurtosis.
- Part II: Laplace probabilities, coin tosses, p-value, urn models, parameter estimation, confidence interval, significance level, alpha and beta errors.
- Part III: Statistical tests, goodness of fit, optimisation methods, how the chi-square and Student’s t-test work (H0/H1 test).
- Mini-assignment: Chi-square goodness-of-fit using a bag of M&Ms as an example. Case study: The travelling salesman problem.
Statistics (English)
- Day 1: Descriptive statistics & relationships between variables (mean, median, quantiles, (co)variance, correlation)
- Day 2: Probability & set theory (random variables, Laplace, urn problem, conditional probability, Bayes’ theorem)
- Day 3: Distributions and graphical representations (discrete/continuous distributions, probability density function, cumulative density function)
- Day 4: Estimates & hypotheses (point & interval estimates, confidence intervals)
- Day 5: Statistical tests and outlook (t-tests, chi-squared tests)