Learn machine learning in R with practical, hands-on instruction. Covers supervised, unsupervised models, interpretability, and evaluation in 40 hours.

Advance your machine learning skills in R with deep learning, Bayesian methods, transformer models, clustering, and anomaly detection in this 28-hour live online course.

Learn Python for data science and statistical computing. Build skills in NumPy, Pandas and visualisation across two days of hands-on training for researchers and analysts.

Machine learning using Python: supervised and unsupervised learning, neural networks, and practical model building with scikit-learn and TensorFlow.

Machine vision using Python: apply deep learning and computer vision with OpenCV and TensorFlow for real-world image classification and ecological data applications.