Statistics: Programming for Data Science

Education facts

Code: STAN48

<p>Want to improve your programming skills and learn how code is used in statistics and data science? This course gives you hands-on experience with R and Python - two of the most widely used languages in modern data analysis.</p><p>This course introduces you to modern statistical programming in data science. You’ll learn how to use R and Python to solve practical problems and implement key statistical methods. Topics include:</p><ul><li>statistical packages and modules in R and Python</li><li>data handling using data frames, arrays and matrices</li><li>random number generation and simulation</li><li>Monte Carlo methods for integration, inference and variance reduction</li><li>bootstrap and other resampling techniques</li><li>Bayesian analysis and MCMC methods</li><li>numerical methods and optimisation.</li></ul>

Entry requirements

90 credits in Statistics, or a total of 90 credits i Mathematics, Programming, Mathematical Statistics and Statistics, of which at least 45 credits in Statistics or Mathematical Statistics, or the equivalent.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Statistics: Programming for Data Science

  Lund University

  Start date: 31 August 2026

  End date: 1 November 2026

  Pace of study: 50 %