FYSS5120 Efficient Numerical Programming (4 cr)

Open the course unit brochure on Sisu

Study level:

Advanced studies

Grading scale:

Pass - fail

Language:

English, Finnish

Responsible organisation:

Department of Physics

Curriculum periods:

2020-2021, 2021-2022, 2022-2023

Description

Python and Julia
Keras and TensorFlow libraries
Efficient C++ programming for applications in science and in mathematics

Calling C++ functions in Python code
Usage of libraries, such as GSL and Boost
Computationally efficient data structures
Pros and cons in operator overloading
Code debugging and identifying of memory leaks

Learning outcomes

At the end of the course students will be able to:

Combine programming with Python and C++
Write C++ code that uses libraries for solving mathematical and physical problems
Understand the layout and inner workings of a C++ code

Keep C++ code and the underlying mathematics in close unison
Hide uninteresting or already well-tested programming details from daily view
Write a machine learning algorithm for data analysis in Python

Description of prerequisites

Programming experience with Python, C++ or some other programming language.

Completion methods

Method 1

Description:

Given every year starting in autumn 2022.

Evaluation criteria:

Accepted solutions to programming assignments.

Time of teaching:

Period 1

Select all marked parts

Parts of the completion methods

Teaching (4 cr)

Type:

Participation in teaching