Data Scientist Specialization (instructor-led)

If you already have experience with machine learning, this advanced, five-segment specialization gets you ready for the higher-level data scientist jobs by taking what you know and building on it. You’ll master skills necessary to become a successful data scientist by working on projects designed by industry experts. Learn to run data pipelines, design experiments, build recommendation systems, and deploy solutions to the cloud.

Key assignments include writing a data science blog post identifying questions about a dataset and analyzing to get your answers. We’ll review essential software engineering skills, such as creating unit tests and building classes; build disaster response pipelines with Figure Eight; and design a recommendation engine with IBM. The specialization culminates with a capstone project incorporating what you’ve learned into a job-ready portfolio piece.


  • Use Python and SQL to access and analyze data from several different data sources
  • Use principles of statistics and probability to design and execute A/B tests
  • Use recommendation engines to assist businesses in making data-automated decisions
  • Deploy a data science solution to a basic flask app
  • Manipulate and analyze distributed datasets using Apache Spark
  • Communicate results effectively to stakeholders


This specialization, estimated to take four months, is an instructor-led format that meets together weekly as an online class to discuss material and assignments.

Month-by-Month Subscription at $899 per month:

This model allows you to pay in full upfront or on a month-by-month basis. Learn more about the subscription model in our FAQ section.


  • Python
  • SQL
  • Statistics

Sections Open for Enrollment:

Open Sections and Schedule
Start / End Date Units Location Cost Instructor
10-05-2020 to 10-31-2020 None ONLINE $899

Jothi Periasamy



Date: Start Time: End Time: Meeting Type: Location:
Mon, 10-05-2020 12:01 a.m. 12:02 a.m. Online Custom ONLINE
Sat, 10-31-2020 11:58 p.m. 11:59 p.m. Online Custom ONLINE

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