Course Learning Objectives:
Knowledge of data analytics is important for many systems engineers, project managers, and project leads. Students successfully completing this course will be able to:
1. Compare and contrast algorithms and processes used for intelligent systems
2. Systematically apply intelligent learning to empirical data
3. Describe the advantages of system approaches to machine learning and artificial intelligence problems.
4. Apply the tools of data analysts, including statistical and software tools
5. Analyze open-ended data analytic challenges in large systems.
This course can be applied toward:
ENGR 530/ECE 530 (Overview of Systems Engineering Processes); ENGR 531/ECE 531 (Engineering Risk Analysis); CIS 600 (Information Technology and Project Management).
Military personnel admitted to a College of Engineering online degree program may be eligible for a 15% tuition discount. Tuition discounts can only be given if you provide the appropriate discount code at the time of registration. Call (877) 491-4336 or email email@example.com to learn more.
Textbooks and Materials
Meta-Algorithmics: Patterns for Robust, Low-Cost, High-Quality Systems (Wiley, 2013), SJ Simske, 384 pp.
Additional information will be available for check out from the professor. Please refer to course syllabus.
Dr. Simske is an HP Fellow and a previous Director in HP Labs. As of September 2016, he is the author of more than 400 publications and roughly 140 US patents (many more worldwide). He is an IS&T Fellow and an honorary professor at the University of Nottingham. Dr. Simske has been a member of the World Economic Forum Global Agenda Councils since 2010, including Illicit Trade, Illicit Economy and the Future of Electronics. At HP, he directed teams in research on 3D printing, education, life sciences, sensing, authentication, packaging, imaging and manufacturing. His book “Meta-Algorithmics” addresses intelligent systems. He is currently co-authoring books on Industrial Inkjet Printing and Meta-Analytics.