STK-INF4000 – Selected Topics in Data Science
Course description
Course content
The course provides insight into selected contemporary relevant topics within Data Science. Students gain practical experience with data analysis and industry relevant algorithms and technologies for data analysis. Course content follows developments in the field.
Learning outcome
After completing the course you will have:
- a general overview of the most contemporary relevant and industry relevant technologies and methods in Data Science;
- theoretical knowledge and practical experience in data analysis and applied statistics;
- experience with the use of distributed systems for storage and / or processing;
- expertise to carry out a real project in data analysis, from data collection to data-driven decision-making guidance;
- learned to reflect on the benefits and the problems inherent in using contemporary current methods in Data Science.
Admission
Students who are admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for in Studentweb.
If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures.
Prerequisites
Recommended previous knowledge
- INF1000 - Introduction to object-oriented programming / INF1100 - Introduction to programming with scientific applications,
- INF2220 - Algorithms and data structures
and / or:
- STK1100 - Probability and statistical modelling,
- STK1110 - Statistical methods and data analysis 1,
- STK2100 - Machine learning and statistical methods for prediction and classification / STK2120 - Statistical Methods and Data Analysis 2 (discontinued),
- STK3100 - Introduction to generalized linear models
Overlapping courses
10 credits overlap with STK-INF3000 – Selected Topics in Data Science (discontinued)
Teaching
3 hours of lectures, 2 hours of open group and oracle services when needed.
The number of groups offered can be adjusted during the semester, depending on attendance.