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Regular version of the site
Master 2022/2023

Intro to Programming in Python

Type: Compulsory course (Science of Learning and Assessment)
Area of studies: Psychology
When: 1 year, 3 module
Mode of studies: distance learning
Online hours: 50
Open to: students of one campus
Instructors: Alena Kulikova (Ponomareva), Mario Martinez-Saito
Master’s programme: Science of Learning and Assessment
Language: English
ECTS credits: 3
Contact hours: 6

Course Syllabus

Abstract

This course is designed to help students with no prior computer programming experience learn to think computationally and write code to solve problems using Python. This course will cover the basics of computing and procedural programming, including mathematical, relational, and logical operators, variables and variable types, the basics of style and commenting, iterative solutions, arrays, matrices and their applications, sorting and searching algorithms, elements of string processing, structures, ways to correctly store and represent information. Students will be able to organize code in functions and save time by writing code that can be reused. Students will learn about Python modules and how to make use of them. Interaction with files using Python is also included in this course. Each topic is illustrated with a set of real-world examples.
Learning Objectives

Learning Objectives

  • Learn the basics of programming in Python.
Expected Learning Outcomes

Expected Learning Outcomes

  • Learn to use numbers, variables, and functions
  • Learn to use Booleans, Strings, Lists, and conditional expressions
  • Learn to control flow
  • Learn the meaning of referencing, scope, and objects
  • Learn typical software engineering approaches
  • Use control flow to process images
  • Manipulate and edit images
  • Learn how to use dictionaries
  • Use dictionaries for data processing
  • Consolidate learned material
Course Contents

Course Contents

  • Expressions and Functions
  • Booleans, If, and Lists
  • Loops
  • References, Objects and Methods
  • Incremental Coding, Iterative Development, Testing & Debugging
  • Nested for loops, 2D Lists and Images
  • Images
  • Dictionaries
  • More Dictionaries and Data Processing
  • Review
Assessment Elements

Assessment Elements

  • non-blocking Course passed
  • non-blocking Course scores
Interim Assessment

Interim Assessment

  • 2022/2023 3rd module
    0.3 * Course scores + 0.7 * Course passed
Bibliography

Bibliography

Recommended Core Bibliography

  • Guido Van Rossum, & Fred L. Drake. (2004). Python/C API Reference Manual Release 2.3.4. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.2FEE239A

Recommended Additional Bibliography

  • Gries, P., Campbell, J., & Montojo, J. (2017). Practical Programming : An Introduction to Computer Science Using Python 3.6 (Vol. Third edition). [Place of publication not identified]: Pragmatic Bookshelf. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1716748

Authors

  • SHALOM KSENIYA VLADIMIROVNA
  • MARTINEZ-SAITO MARIO -