Data Analytics II (AI for Climate Change)

Module code: BUSM235

Credits: 15.0
Semester: SEM2

Contact: Dr Nataliia Efremova

Data analytics 2 course is a core module that introduces advanced concepts of artificial intelligence and machine learning. Students will learn the following machine learning methods: computer vision with convolutional neural networks, time series analysis with long-short term memory networks, generative adversarial networks for data augmentation and data fusion from different sources.
Alongside with studying theoretical aspects of machine learning, students will have an opportunity to apply these methods to climate-related data: historical weather data, ground measurements and satellite imagery. Students will learn how to download and process satellite imagery and provide quantitative analysis of this data to solve a variety of climate-related problems.

Connected course(s): UDF DATA
Assessment: 60.0% Examination, 40.0% Coursework
Level: 7