Data Science Certification

Experfy in Harvard Innovation Labs, in collaboration with the industry, prepares you for a career as a Data Scientist.

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Specialization fact course
5 Self-paced Courses

Designed to ensure you learn the fundamental skills to embark on a career as a Data Scientist.

Specialization fact instructor
Learn From the Best

A stellar team of academics at Harvard and Columbia, and industry practitioners at Cisco, Nokia Labs and Pitney Bowes.

Specialization fact certificate
Certification

Industry recognized certification enables you to add this credential to your resume upon completion of all courses.

Data Science Training Track

Learn data science from industry experts at Harvard, Columbia, Cisco, Apple and Google. Experfy instructors are industry thought leaders who provide you with in-depth training in introductory topics like statistics to advanced ones like machine learning. This Data Science Certification Program covers the concepts and tools you will need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. As you work your way through different courses in the data science training track, you will develop a portfolio of projects that you can showcase during interviews.  Employers want to see students who have been trained by real experts and not by training departments. Experfy courses give you the practical hand-on training that will prepare you for the real world skills that will be necessary as you begin working as a data scientist.

Probability and Statistics for Data Science with R

  • Kaitlin Hagan, Instructor - Probability and Statistics for Data Science with R Kaitlin Hagan, 
  • Michael Parzen, Instructor - Probability and Statistics for Data Science with R Michael Parzen

Self-paced

Course 1
About the Course
  • Harvard faculty teaches you how to apply statistical methods to explore, summarize, make inferences from complex data and develop quantitative models to assist business decision making.
  • Course includes instructional component, R tutorial videos, and exercises to reinforce concepts and give you an opportunity to see statistics in action.
  • Michael Parzen is an award-winning faculty member at Harvard and teaches one of the most popular classes. Kaitlin Hagan is a post-doctoral fellow at Brigham and Women's Hospital and has won numerous teaching awards and citations for her work.

Data Wrangling in R

  • Dr. Connie Brett, Instructor - Data Wrangling in R Dr. Connie Brett

Self-paced

Course 2
About the Course

Real-world data preparation for further analysis using R

  • Learn from start to finish how to get your data into R efficiently and polish it up so that it is as good as it can be.
  • Instructor is the founder of Analytics Incubation Center at Cisco and has 15 years of analytics development experience.
  • Capstone project reviewed by the instructor.

Econometric Analysis: Methods and Applications

  • Alan Yang, Instructor - Econometric Analysis: Methods and Applications Alan Yang

Self-paced

Course 3
About the Course
  • Quantitative and econometric analysis focused on practical applications that are relevant in fields such as economics, finance, public policy, business, and marketing. 
  • The Instructor, Alan Yang, is a faculty member at the Department of International and Public Affairs at Columbia University where he teaches courses in Introductory Statistics, Econometrics, and Quantitative Analysis in Program Evaluation and Causal Inference.

Classification Models

  • Saed Sayad, Instructor - Classification Models Saed Sayad

Self-paced

Course 4
About the Course

How to use classification algorithms to solve real world problems

  • Online self-paced course with cap-stone project 
  • Instructor is lead data scientist at one of the largest software companies in the world, author of a best-seller and an adunct professor at University of Toronto

Clustering and Association Rule Mining

  • Anirban  Ghosh, Instructor - Clustering  and Association Rule Mining Anirban Ghosh

Self-paced

Course 5
About the Course

Learn Clustering methods and Association Rule Mining Techniques

  • Learn concepts of Cluster Analysis and study most popular set of Clustering algorithms with end-to-end examples in R
  • Supported by office hours and hands-on practice exercises to be submitted at the end of the course 
  • Instructor:Machine Learning Scientist with 9+ years of hands-on experience in predictive analytics domain at companies like Target, Symphony-IRI and Genpact

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Toll Free: (844) EXPERFY OR (844) 397-3739

Email: support@experfy.com

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