MST 0050 Mathematics and Statistics for Data Science

Reading material

Exams

Lecture plan Autumn 2026

Mathematics Lecturer Eivind Eriksen (Office B3y-085); Office hours TBA Reading: Exercises:
Mon Aug 17: 09-12, C2-095 Lecture 1: Linear systems and Gaussian elimination. Rank. [E] 1.1 - 1.6 Problem set 1
Tue Aug 18: 14-17, C2-095 Lecture 2: Span and linear Independence. Orthogonal projection. [E] 2.1 - 2.7 Problem set 2
Mon Aug 24: 09-12, C2-095 Lecture 3: Matrices, determinants and minors. [E] 3.1 - 3.4 Problem set 3
Tue Aug 25: 14-17, C2-095 Lecture 4: Eigenvalues and eigenvectors. Diagonalization. [E] 4.1 - 4.4 Problem set 4
Mon Aug 31: 09-12, C2-095 Lecture 5: Orthogonal diagonalization. Quadratic forms. [E] 4.4 - 4.6 Problem set 5
Mon Sep 07: 09-12, C2-095 Lecture 6: Unconstrained Optimization. Convexity. [E] 5.1 - 5.6 Problem set 6
Mon Sep 14: 09-12, C2-095 Lecture 7: Constrained Optimization. Lagrange problems. [E] 6.1 - 6.4 Problem set 7
Mon Sep 21: 09-12, C2-095 Lecture 8: Kuhn-Tucker problems. Minimum variance portfolios. [E] 6.5 Problem set 8
Mon Sep 28: 09-12, C2-095 Lecture 9: Envelope theorems. Examples. [E] 5.7, 6.6 - 6.7 Problem set 9
Statistics Lecturer Jonas Moss (Office B3-071); Office hours TBA Reading: Exercises:
Mon Oct 05: 14-17, C2-095 Lecture 1: Statistics See Canvas
Mon Oct 12: 14-17, C2-055 Lecture 2: Statistics See Canvas
Mon Oct 19: 14-17, C2-055 Lecture 3: Statistics See Canvas
Mon Oct 26: 14-17, C2-095 Lecture 4: Statistics See Canvas
Mon Nov 02: 14-17, C2-095 Lecture 5: Statistics See Canvas
Mon Nov 09: 14-17, C2-055 Lecture 6: Statistics See Canvas

Thu Dec 03 (not confirmed) Home exam (40%)
Mon Dec 07 (not confirmed) Final exam (60%)