Build foundational knowledge of data science with this introduction to probabilistic models, including random processes and the basic elements of statistical inference. The world is full of uncertainty: accidents, storms, unruly financial markets, noisy communications. The world is also full of data. Probabilistic modeling and the related field of [...]
Learn how to apply statistical modelling techniques to real-world business scenarios using Python. In this course, you will learn three predictive modelling techniques - linear and logistic regression, and naive Bayes - and their applications in real-world scenarios. The first half of the course focuses on linear regression. This [...]
Learn about manufacturing systems and ways to analyze them in terms of material flow and storage, information flow, capacities, and times and durations of events, especially random events. In this course you will learn how to analyze manufacturing systems to optimize performance and control cost. You will develop an [...]
This course provides an introduction to basic probability concepts. Our emphasis is on applications in science and engineering, with the goal of enhancing modeling and analysis skills for a variety of real-world problems.
A hands-on introduction to basic programming principles and practice relevant to modern data analysis, data mining, and machine learning. The modern data analysis pipeline involves collection, preprocessing, storage, analysis, and interactive visualization of data. In the course, you’ll see how computing and mathematics come together. [...]