ENGM 5100 - Data Analytics for Engineering Managers

(3) Credit Hours

Introduction to the field of data mining and machine learning applications for engineering managers. Topics covered include data extraction, data cleaning, data profiling, data visualization, designing data processing pipelines including data transformation and standardization models, probability and regression models, the application of supervised and unsupervised learnings including the use of Naïve Bayes, Support Vector Machine, K-Means Approach, K Nearest Neighbor, Decision Trees on real-life data. Emphasis on applying the concepts and the techniques via Alteryx and Tableau using real data to help engineering managers make effective data-driven decisions. Communication of business insights using real data, in both written and oral presentations. Project required. Spring semester. Pre or Corequisites: ENGM 5030 or department head approval. Differential Course Fee will be assessed.