JBP020 :Programming

Algemeen

Voertaal Engels
Werkvorm: (2 hour) Lectures and (2/3 hours) labs (Collegerooster)
Tentamenvorm: Written exam (70%) + 2 individual assignments (2x 15% =30%) (Tentamenrooster)
Niveau:Bachelor
Studielast:6 ECTS credits
Blackboard informatieniet beschikbaar in Blackboard

Docent(en)


drs. M.J.H. van den Hoogen MSc (Coördinator)

N.R. Claus MSc (Support)


Doel van de cursus (alleen in het Engels beschikbaar)

The course gives students who do not have experience with programming, a first introduction and basic skills in (mainly imperative) programming and scripting, using Python 3.

The student can solve simple programming problems independently, and structure these in the language Python. Most of the learned principles can be applied to other computer languages used in data science (e.g. R) as well.


Inhoud van de cursus (alleen in het Engels beschikbaar)

  • Expressions, assignment, statements
  • Basic datatypes
  • Control structures (e.g. conditional execution, loops)
  • Using and defining functions
  • Lists / composite datatypes (e.g. dictionaries, tuples)
  • Comprehensions
  • Files, text I/O, reading and handling data in a machine readable format (e.g. CSV or JSON)
  • Exceptions, assertions
  • Debugging
  • Basic knowledge of objects and methods
  • Modules
  • Algorithms


Bijzonderheden (alleen in het Engels beschikbaar)

Literature

Lectures notes will be provided after each lecture in the form of "Jupyter Notebooks". In addition, we will use the book "How to think like a computer scientist: Learning with Python 3", which is available online free of charge. (A blend of) other articles, class notes and/or material may be used.

Students who want an additional 'paper' book to read up on several Python programming topics, may consider Python Programming: An introduction to computer science by John Zelle (3rd edition). The course is not dependent on that book though.

Grading

The average grade of the two individual assignments has to be 5.0 at a minimum to be admitted to the final exam. To pass the course, a 5.5 total score (based on 70% exam, 30% for the assignments) is required and the grade for the written exam should be 5.0 at a minimum (if the grade for the exam is below 5.0, the final course grade will be capped at a grade of 5 maximum).

As of January 31st, 2018: the grade (total score) will be 100% based on a final exam. To pass the course, a 5.5 (or higher) score is required.

Admission and location

The courses from the Data Science and Entrepreneurship program require specific prior knowledge. It is only possible to participate in this course if approved by the admission committee and if you are enrolled for the program.

Please note that this course will be taught in Mariënburg, ‘s-Hertogenbosch (JADS).


Verplichte literatuur

  1. Allen (B.) Downey, Think Python: How to Think Like a Computer Scientist (2nd edition, Python 3; available free of charge online), Green Tea Press, 2015, ISBN 2nd edition.
  2. A blend of class notes and (possibly) material from reference books and/or research articles will be used.


Vereiste voorkennis


Mogelijk interessant voor

  • Pre-master Data Science and Entrepreneurship ( 2016, 2017 )

(05-jan-2018)