Introduces the tools of statistical analysis. Combines theory with extensive data collection and computer-assisted laboratory work. Develops an attitude of mind accepting uncertainty and variability as part of problem analysis and decision-making. Topics include: exploratory data analysis and data transformation, hypothesis-testing and the analysis of variance, simple and multiple regression with residual and influence analyses.
| Day | Start Time | End Time | Room |
|---|---|---|---|
Tuesday | 12:10 | 13:30 | C-302 |
Friday | 12:10 | 13:30 | C-302 |
Wednesday | 15:20 | 16:40 | PL-2 |
Introduces the tools of statistical analysis. Combines theory with extensive data collection and computer-assisted laboratory work. Develops an attitude of mind accepting uncertainty and variability as part of problem analysis and decision-making. Topics include: exploratory data analysis and data transformation, hypothesis-testing and the analysis of variance, simple and multiple regression with residual and influence analyses.
| Day | Start Time | End Time | Room |
|---|---|---|---|
Monday | 12:10 | 13:30 | C-302 |
Wednesday | 12:10 | 13:30 | PL-2 |
Thursday | 12:10 | 13:30 | PL-2 |
This project-based course introduces data science by looking at the whole cycle of activities involved in data science projects. Students will learn how to think about problems with rigor and creativity, ethically applying data science skills to address those problems. The course project will address the theoretical, mathematical and computational challenges involved in data science.
| Day | Start Time | End Time | Room |
|---|---|---|---|
Tuesday | 10:35 | 11:55 | C-302 |
Friday | 10:35 | 11:55 | C-302 |
Familiarizes students with several types of multivariate statistics methods with respect primarily to applications and interpretations in the area of social sciences. This course will cover the data-analysis concepts and procedures used in applied and experimental psychology, economics, business and in general in social sciences. Emphasis will be given to the qualitative interpretation and manipulation of mathematical and statistical concepts, showing the students their effectiveness through concrete applications. Students will use appropriate software packages for labs and projects.
| Day | Start Time | End Time | Room |
|---|---|---|---|
Monday | 13:45 | 15:05 | C-302 |
Wednesday | 13:45 | 15:05 | C-302 |
Thursday | 13:45 | 15:05 | C-302 |
The 21st century has seen a big increase in the amount of data which is made accessible. Social media such as Facebook, online shops such as Amazon and many others, are all gathering raw data. But what can be done about this data? Data Science covers tools and methods around the extraction of knowledge from data. Such tools cover its collection, storing, processing and analysis. In this course we will learn about several of the most important tools in the above flow and will apply them to real-world examples.
| Day | Start Time | End Time | Room |
|---|---|---|---|
Monday | 10:35 | 11:55 | C-302 |
Wednesday | 10:35 | 11:55 | C-302 |
Thursday | 10:35 | 11:55 | C-302 |
Topics vary by semester
| Day | Start Time | End Time | Room |
|---|---|---|---|
Tuesday | 13:45 | 15:05 | Q-604 |
Friday | 13:45 | 15:05 | Q-604 |
This course joins two seemingly disparate disciplines – law and science – in an attempt to understand more fully the dense, multidimensional nature of the digital revolution and how we are going to live with it. Human Rights and Digital Technology is designed as an interdisciplinary primer, a guide to examining the critical issues that shape our use of digital technology.
| Day | Start Time | End Time | Room |
|---|---|---|---|
Tuesday | 13:45 | 15:05 | Q-604 |
Friday | 13:45 | 15:05 | Q-604 |
This multi-workshop style course provides students with the possibility to exchange with internationally renowned industry and academic experts. Students will learn how data science is applied in industry, international organizations and research institutions. They will be exposed to various career paths and become acquainted with the requirements, future developments, challenges and opportunities within different organizations and application area.
| Day | Start Time | End Time | Room |
|---|---|---|---|
Monday | 15:20 | 18:15 | Q-609 |
Tuesday | 15:20 | 18:15 | Q-609 |
Friday | 15:20 | 18:15 | Q-609 |
Tuesday | 09:00 | 10:20 | Q-609 |
Friday | 09:00 | 10:20 | Q-609 |
The 21st century has seen a big increase in the amount of data which is made accessible. Social media such as Facebook, online shops such as Amazon and many others, are all gathering raw data. But what can be done about this data? Data Science covers tools and methods around the extraction of knowledge from data. Such tools cover its collection, storing, processing and analysis. In this course we will learn about several of the most important tools in the above flow and will apply them to real-world examples.
| Day | Start Time | End Time | Room |
|---|---|---|---|
Monday | 10:35 | 11:55 | C-302 |
Wednesday | 10:35 | 11:55 | C-302 |
Thursday | 10:35 | 11:55 | C-302 |
Following the first data protection course, this course guides students through the preparation of the Certified Information Privacy Manager (CIPM) certification offered by the International Association of Privacy Professionals (IAPP). At the end of the course, students may take the IAPP certification exam. The IAPP’s CIPM is a widely recognized privacy certification for professionals seeking to fulfill roles such as data protection officer, data and AI officer, data ethics office, data protection manager, etc.
| Day | Start Time | End Time | Room |
|---|---|---|---|
Monday | 18:30 | 19:50 | Q-609 |