• To acquire knowledge on the fundamentals of IoT systems and their hardware and software requirements.
• To acquire knowledge on the fundamentals of data science including Bayesian statistics, supervised and unsupervised machine learning.
• To acquire skill and hands on experience in deploying data science algorithms on real-world data for IoT applications.
This module covers data science for the Internet of Things. The topics include data science fundamentals such as Bayesian statisitcs, classification, supervised learning, unsupervised learning, and deep learning. The module will also cover several basic machine learning algorithms such as decision trees, logistic regression, support vector machines, and neural networks. Students will visualize and analyze real-world data sets via practical IoT case studies.