Programming in Python (3306)
  
Coordinating lecturer :Prof. dr. Bart MOELANS 
  
Co-lecturer :Prof. dr. Frank NEVEN 
  
Member of the teaching team :De heer Dante PINTO ARAYA 

Language of instruction : English
Credits: 5,0
  
Period: semester 1 (5sp)
  
2nd Chance Exam1: Yes
  
Final grade2: Numerical
 
Exam contract: not possible
 
Sequentiality
 
   No sequentiality

Content

A program is an algorithm that can be directly executed by a computer. Learning to program therefore encompasses two complementary skills: (1) constructing algorithms; (2) coding an algorithm as a program. This course focuses on both aspects. We will use the programming language Python.

In particular, this course has the following goals:

  • The student can write simple imperative programs in Python. In particular, he/she can utilize primitive types, strings, lists, iteration, conditions, procedures and functions.
  • The student understands the importance of precise syntax and semantics.
  • The student is able to reason about programs and can debug programs.
  • The student is familiar with the notion of an algorithm, can devise algorithms (for simple problems), and can reason over algorithms.
  • The student is familiar with the principles of computational thinking and can apply these.


Organisational and teaching methods
Organisational methods  
Lecture ✔  
Self-study assignment ✔  
Small group session ✔  


Evaluation

Semester 1 (5,00sp)

Evaluation method
Written evaluation during teaching period30 %
Transfer of partial marks within the academic year✔
Homework✔
Written exam70 %
Proficiency test✔
Evaluation conditions (participation and/or pass)✔
Conditions

A minimum score of 40% on each of the two components of the evaluation (assignments and final exam) is required to pass the course.
Consequences

The student will receive a score of maximum 8/20.

Second examination period

Evaluation second examination opportunity different from first examination opprt
No
Explanation (English)The permanent evaluation (30% of end score) can not be redone.
 

Compulsory textbooks (bookshop)
 

Textbook 1:

Intro to Python for computer science and data science, Paul Deitel and Harvey Deitel

ISBN: 9780135404676
 

Recommended course material
 

Visual Studio Code (https://code.visualstudio.com/) is recommended software for this course. 


Learning outcomes
Master of Statistics and Data Science
  •  EC 

    • The student is able to efficiently acquire, store and process data.

     
  •  DC 
    		• ...maintain provenance of data, analyses and results
  •  EC 

    • The student is capable of acquiring new knowledge.

 
  EC = learning outcomes      DC = partial outcomes      BC = evaluation criteria  
Offered inTolerance3
1st year Master Bioinformatics J
1st year Master Bioinformatics - icp J
1st year Master Biostatistics J
1st year Master Data Science N
1st year Quantitative Epidemiology J
Exchange Programme Statistics J



1   Education, Examination and Legal Position Regulations art.12.2, section 2.
2   Education, Examination and Legal Position Regulations art.15.1, section 3.
3   Education, Examination and Legal Position Regulations art.16.9, section 2.