Certificate: Data Science

Data is everywhere—from e-commerce sales, app downloads to a smartphone, to supply chain management or bioinformatics or connected devices. And that massive increase in the amount and variety of data being collected is translating to an exponential growth in the computer power needed to process that data.

In addition, there continues to be an incredible need for data scientists to make sense of the numbers and uncover hidden solutions to messy business problems. With the Certificate Program in Data Science, you gain the skills to perform advanced data wrangling, data mining, statistical modeling, and machine learning on data sets that may be very large and complex.

Curriculum Requirements

The curriculum comprises one core course, one programming course, one machine learning course, and up to four units of electives for a total of 10-semester units (150 hours of instruction). You must pay a nonrefundable certificate application fee.

You must take all courses for a letter grade. To receive the certificate, you must maintain an overall minimum 2.5-grade point average (GPA), with a grade of C or better (no C-minus grades) in each course. A Certificate With Distinction will be awarded to those who complete the certificate with a GPA of 4.0 (effective to those who register beginning Jan. 2, 2018).

All coursework must be completed within three years. However, requirements may be updated based on new developments in the field of study; we recommend completing the curriculum in a timely fashion.

Certificate and Award Request

Once you have complete the certificate coursework, notify UC Berkeley Extension that you have completed the curriculum and request your certificate. Send an email to [email protected]. After your records have been reviewed, verified, and approved (usually within two to three weeks), your certificate will be mailed to you.

Courses

Programming

You take at least one of the following Programming courses.

• Introduction to R: Data Exploration and Visualization
• Python for Data Analysis and Scientific Computing
• Introduction to Data Science
• Introduction to Data Science Using R

Machine Learning

You take at least one of the following Machine Learning courses.

• Introduction to Machine Learning Using Python
• Machine Learning and Deep Learning With Spark
• Practical Machine Learning (With R)
• Machine Learning With TensorFlow

Core Courses

• Students must take at least one Core Course.
• Practical Statistics for Data Scientists Using R
• Introduction to Big Data
• Data Science Principles and Practice Using Python
• Data Visualization

Electives

Round out your learning with two of the following courses. You also have the option to take additional courses in the Programming and Machine Learning categories to fulfill the 10-semester units requirement.

• Introduction to Databases
• Introduction to SQL

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