Course ObjectiveSkills for AI is a brush up course for students with limited background
in linear algebra, logic and programming skills. This courses has three
1. express logical statements in propositional and predicate logic
2. reason about the meaning of such formulas through truth tables and
3. argue formally whether one formula implies another one
4. reduce a propositional formula to disjunctive or conjunctive normal
After successfully completing this part,
- the student has a working knowledge of the concepts of matrix
algebra and finite-dimensional linear algebra, such as linear
- the student is familiar with the general theory of finite
dimensional vector spaces, in particular with the concepts of basis and
After this course the student should be able to write a computer
program in Python, using types (int, boolean, float, list and str),
expressions, assignment statements, if-statements, iterations (while-
and for-statements), using standard functions, using module math,
making functions, and performing I/O, matrices and recursion.
This course contributes to exit qualifications in terms of the Dublin
descriptors "Knowledge and understanding" and "Applying knowledge and
Course ContentThis brush up course contains three modules: logic, linear algebra, and
The logic part focuses on propositional logic: truth tables, boolean
operators, functional completeness, logical puzzles. In addition the
student will learn the meaning and use formulas of predicate logic, to
express mathematical properties and sentences from natural language.
The main topics are: systems of linear equations, linear (in)dependence,
linear transformations and matrices, matrix operations, determinants,
vector spaces and subspaces.
During this part, students learn to solve problems using structured
programming. As a side effect, students learn Python, as this is the
programming language in which they practice structured programming.
Teaching MethodsLectures, and practical sessions,
Method of Assessmentwritten exam, practical assignments for programming
LiteraturePart 1 Logic: All course materials will be provided via Canvas.
Part 2 Linear algebra: All course materials will be provided via
(Linear Algebra and its Applications, by David C. Lay, Steven R. Lay en
Judi J. McDonald, global edition (fifth edition), Pearson.)
Part 3 Programming: An on line book is used (How to Think Like a
Computer Scientist, Learning with Python, 2nd Edition, by Jeffrey
Elkner, Allen B. Downey,
and Chris Meyers) see the URL:
Target AudienceOnly first year master AI students without an Artificial
Intelligence/Computer Science bachelor degree can attend this course.
|Language of Tuition||English|
|Faculty||Faculty of Science|
|Course Coordinator||dr. A.C.M. ten Teije|
|Examiner||dr. A.C.M. ten Teije|
dr. A.C.M. ten Teije
You need to register for this course yourself
Last-minute registration is available for this course.
|Teaching Methods||Study Group, Lecture|