Advanced programming in Python

<p>The course starts with a quick introduction to the elements of Python, which serves as repetition for students who already know Python but also enables students with other backgrounds to get started with Python.<br /> <br /> After the introduction, the course proceeds to more advanced features of Python programming:</p> <ul> <li>object-oriented design</li> <li>functional programming techniques</li> <li>advanced Python-specific techniques</li> <li>the use of standard libraries</li> <li>testing methodologies</li> <li>creation of larger programming projects</li> </ul> <p>The goal is to give a thorough understanding of Python so that the participants can read and write state of the art code and reason about design choices.<br /> <br /> The theoretical material is presented in relation to a project, which is divided into individual components (labs), and which results in a comprehensive software system implementing techniques such as scientific computing, data analysis, visualization, and machine learning. No knowledge of these techniques is presupposed but will be a part of the teaching; the focus here is not on the theory but on enabling the students to use relevant software libraries in adequate ways.<br /> <br /> <em>Sub-courses</em><br /> <strong>1. Written hall examination </strong><em>(Skriftlig salstentamen)</em>, 3 credits<br /> Grading scale: Pass with distinction (5), Pass with credit (4), Pass (3) and Fail (U)<br /> <br /> <strong>2. Laboratory work</strong> <em>(Laboration)</em>, 4.5 credits<br /> Grading scale: Pass with distinction (5), Pass with credit (4), Pass (3) and Fail (U)</p>