DAMSL-100 Introduction to Data Science
Type
Core
Course Code
DAMSL-100
Teaching Semester
B semester
ECTS Credits
10
Syllabus
- Sampling data
- Statistical learning
- Linear regression
- Classification
- Resampling methods
- Linear model selection and regularization
- Beyond linearity
- Tree-based methods
- Survival analysis and censored data
- Unsupervised learning
Learning Outcomes
Upon completion of the course the students will be able to:
- To understand the basic ideas and concepts in Data Science
- Comprehend basic sampling methods
- Conduct basic data analysis
- Know the basic regression and classification algorithms
- Know survival analysis
- Know basic unsupervised learning methods
Student Performance Evaluation
Homework and/or Lab Assignments, Final Exam and/or Project
Prerequisite Courses
Linear Algebra I, Probabilities