Online courses directory (209)
This is a mostly self-contained research-oriented course designed for undergraduate students (but also extremely welcoming to graduate students) with an interest in doing research in theoretical aspects of algorithms that aim to extract information from data. These often lie in overlaps of two or more of the following: Mathematics, Applied Mathematics, Computer Science, Electrical Engineering, Statistics, and / or Operations Research.
The main goal of this course is to study the generalization ability of a number of popular machine learning algorithms such as boosting, support vector machines and neural networks. Topics include Vapnik-Chervonenkis theory, concentration inequalities in product spaces, and other elements of empirical process theory.
This course gives an introduction to probability and statistics, with emphasis on engineering applications. Course topics include events and their probability, the total probability and Bayes' theorems, discrete and continuous random variables and vectors, uncertainty propagation and conditional analysis. Second-moment representation of uncertainty, random sampling, estimation of distribution parameters (method of moments, maximum likelihood, Bayesian estimation), and simple and multiple linear regression. Concepts illustrated with examples from various areas of engineering and everyday life.
This follow-on course takes you deeper into the workings of Google Analytics and provides comprehensive training for marketers and data analysts seeking to understand the core principles of digital analytics and how to improve web site performance through better data measurement. Google Analytics is a service offered by Google that generates detailed statistics about a web site's traffic and sources and it also measures conversions and sales. It can track visitors from all referrers, including search engines and social networks, direct visits and referring sites. It also displays advertising, pay-per-click networks, email marketing and digital collateral such as links within PDF documents. In this free online course you will be guided on how to build an effective measurement plan and what the best practices for collecting actionable data are. You will learn about key digital measurement concepts, terminology and analysis techniques, and the role of reports in Google Analytics, with specific examples for evaluating your digital marketing performance. This course will be of great interest to all marketing and data analysis professionals who would like a better understanding of how data analysis can improve web site performance, and to all learners who would like to learn more about Google Analytics.<br />
In this education and teacher training course, the case for using multiple choice exams for science and engineering courses is made. Multiple-choice exams effectively assess student learning in engineering and science courses and are more objective than other types of exams.
Learn how to conduct effective and systematic design of exam questions.
Using psychometrics statistics, you will be able to analyze the results and improve the performance of your exams.
Finally, you will learn how to build, use and maintain a database of multiple choice exam questions for easy administration and review of exams and their performance results.