About this course: Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems. At the end of the course, you will be able to: • Design an approach to leverage data using the steps in the machine learning process. • Apply machine learning techniques to explore and prepare data for modeling. • Identify the type of machine learning problem in order to apply the appropriate set of techniques. • Construct models that learn from data using widely available open source tools. • Analyze big data problems using scalable machine learning algorithms on Spark.
Who is this class for: This course is for those new to data science. Completion of “Big Data Integration and Processing” is recommended. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Refer to the specialization technical requirements for complete hardware and software specifications.
Taught by: Mai Nguyen, Lead for Data Analytics
San Diego Supercomputer Center
Taught by: Ilkay Altintas, Chief Data Science Officer
San Diego Supercomputer Center
| Basic Info |
Course 4 of 6 in the
Big Data Specialization.
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| Commitment | 5 Weeks, 3 - 5 hours per week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
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| Audit | Purchase Course | |
|---|---|---|
| Access to course materials | Available | Available |
| Access to graded materials | Not available | Available |
| Receive a final grade | Not available | Available |
| Earn a shareable Course Certificate | Not available | Available |
One of the best courses in the series with a good mix of theory and hand-on exercise on ML implementation in big data
Great overview about the machine learning in general. There are still lots not covered specially the Neural Network algorithms. Learning Spark MLlib was great advantage of this course.
Best course so far in this Intro to Big data.
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very easy to follow and good hand on exercise