Python or R? Learn both, and stop guessing.

Researchers waste a lot of time on this question. One colleague swears by R, another by Python, and the honest answer is that each is better at different parts of the job. This course teaches you both from installation onwards, and shows you where each one earns its place.

You will start by setting up Miniconda, Jupyter and R, then cover the fundamentals in parallel - data types, control flow, functions, modules and packages in both languages. From there into the work researchers actually do: file handling and directories in Python, importing, exporting and manipulating data in R.

The statistics your research needs

NumPy and SciPy in Python, and in R the tests you will be asked for in review: descriptive statistics, correlations, t-tests, ANOVA and multiple linear regression. Then visualisation - three lectures on Matplotlib, plus basic and advanced plotting in R, animated graphs, report generation, and wind rose plots (with a homework exercise using real data from the Erbil station).

Three full case studies

• Leaf Area Index and Land Surface Temperature from satellite data

• Analysing India's air quality data with machine learning, across four lectures

• Climate data analysis, across four lectures

There is also an introduction to artificial intelligence, deep learning in R, geospatial data processing in Python, and calculating remote sensing indices.

What you get

• Over five hours across 56 lectures, taught in both languages

• Seven quizzes and a practice test

• Real research data, not toy examples

• Code you can adapt straight into your own work

Before you enrol

No programming experience is needed - both languages start from installation. The installation lectures are recorded on Windows, though the code runs on macOS and Linux as well. Everything used is free.

Taught by Dr. Azad Rasul, a geospatial data scientist and Assistant Professor, with over 150,000 students enrolled across his Udemy courses.

Enrol now and start analysing your research data in the language that suits it.