This is a follow up post to our earlier posts about two freely available Massive Open Online Courses (MOOCs) we offered this summer as part of the BerkeleyX Big Data XSeries. The courses were the result of a collaboration between professors Anthony D. Joseph (UC Berkeley) and Ameet Talwalkar (UCLA) with generous sponsorship by Databricks. We are pleased to report that we have completed the first successful runs of both courses, with highly positive student feedback along with enrollment, engagement, and completion rates that are two to five times the averages for MOOCs.
The first course, CS100.1x Introduction to Big Data with Apache Spark, introduced nearly 76,000 students to data science concepts and showed them how to use Spark to perform large-scale analyses through hands-on programming exercises with real-world datasets. Over 35% of the students were active in the course and the course completion rate was 11%. As an alternative to Honor Code completion certificates, we offered a $50 ID Verified Certificate option and more than 4% of the students chose this option. Over 83% of students enrolled in the Verified Certificate option completed the course.
The second course, CS190.1x Scalable Machine Learning, leveraged Spark to introduce students to the underlying statistical and algorithmic principles required to develop scalable machine learning pipelines. This course also had notably high enrollment (50K), completion rate (15%), percentage of Verified Certificate students (6%), and completion rate for verified students (88%). Overall, 1,800 students earned verified certificates for both courses and received a BerkeleyX Big Data XSeries Certificate.
Stay tuned for announcements about future runs of these and follow-up MOOCs!