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732A74 Introduction to Python

Python is one of the most popular programming languages today, both for general applications and for data science. The goal of this course is to give an introduction to the language, programming paradigms used and some popular libraries.

Intended learning outcomes

On completion of the course, you should be able to:

  1. be ready to write computer code for scientific computing using basic Python language elements
  2. use simple and advanced data structures for problem solving
  3. apply tools available in some commonly used Python packages
  4. correct mistakes in own code

For each learning objective, there is a set of more specific knowledge requirements that outline what you need to demonstrate in order to earn a certain grade. These knowledge requirements are listed on the Examination page.

Course content

The course covers the following content:

  • Python basics: programming environment and documentation, program flow, variables, comments, numerical operators, loops, conditional statements.
  • Data structures: simple data types, tuples, lists, dictionaries, sets, iterators and generators.
  • Functions and functional programming, anonymous lambda functions, comprehensions.
  • Classes and object oriented programming, objects and message passing
  • The standard library, and touching upon essential third-party packages for graphics, scientific computing and data manipulation.
  • Debugging.

Teaching and working methods

The course is taught in the form of lectures and lab sessions. You are also expected to study independently, both individually and in groups. When you plan your time for the course, you should calculate approximately

  • 20 hrs to prepare for, attend, and follow-up on the lectures
  • 60 hrs to prepare for, carry out, and follow-up on the labs

3hp corresponds to 80 hours of work, and we expect you to put in as much, if needed.

Course literature

There is no obligatory textbook for the course. There are a large number of sources for information about Python online, the books by Mark Lutz are a good starting point if one wants something printed.

For those with a special interest in Python as a language, or languages as such, Fluent Python might be worth looking at. Note that it does not fulfil the same need as eg an introductory book aimed at teaching experienced programmers the language.

Feedback policy

What you can expect from us. We try our best to give you prompt, constructive, and meaningful feedback on how well you meet the knowledge requirements set out for the course. We offer feedback in various forms; you can find detailed information about this on the Examination page. Our focus is on non-examinatory, formative feedback, which you can use to improve your learning (and we can use to improve our teaching!) while the course is ongoing.

What we expect from you. We expect you to familiarise yourself with the knowledge requirements set out for the course, and to actively seek our feedback on how well you meet these requirements. We also expect you to reflect on the feedback that we provide, and to grasp opportunities to put it to good use.

Communication policy

What we expect from you. This webpage is the primary source of information about the course, and we expect you to keep yourself up-to-date with what we publish here. We also send out information via the University’s email list for the course, and we expect you to subscribe to this list and read your email on a regular basis while the course is ongoing. Check whether you are subscribed

What you can expect from us. When you contact us via email, you can not expect an answer outside standard working hours, 8–17. (We do not respond to email in the evening or on a weekend.) For a more personal contact, you can contact one of the teachers to set a meeting.

Page responsible: Anders Märak Leffler
Last updated: 2019-01-22