Big data, analytics, and cloud computing; data preparation: organization, basic statistics, cleaning, and integration; data mining techniques: pattern mining, classification, clustering, outlier and anomaly detection; model evaluation; data warehousing and multi-dimensional analysis; data visualization and visual data analytics.
I took the course Winter 2017 and it was the first semester the course was offered. Viktor is an amazing prof and made the class extremely enjoyable; she definitely knows her stuff. The content can be somewhat challenging at times, but the course expectations are clear and overall I found myself learning a lot of useful, relevant material. This was a grat intro to data science.
I WOULD recommend this course to others.
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