Data Science Training and Certification

Data wrangling, exploration, modeling, validation, visualization, and communication. Based on industry use cases by Experfy in Harvard Innovation Lab

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Track fact market
Big Data annual spending to reach $48.6 billion by 2019

International Data Corporation

Track fact sallary
Average annual salary for a Big Data Scientist is $123,000

Indeed Salary Search

Track fact job
190K data scientist jobs by 2018

McKinsey Global Report

Data Science Training Track

Learn data science from industry experts at Harvard, Columbia, Cisco, Apple and Google. Whether you’re new to the field or looking for additional training, we have introductory, advanced, and industry-specific courses to meet your learning goals.  There are no shortcuts to preparing yourself to become a data scientist.  Experfy instructors are industry thought leaders who provide you with in-depth training in introductory topics like statistics to advanced ones like machine learning. Ask the right questions, manipulate data sets, and create visualizations to communicate results. This data science training and certification track 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.

Demand for Data science talent is exploding. Once you complete the training track on data science, you will know how to build and derive insights from data science and machine learning models. You will learn key concepts in data acquisition, preparation, exploration and visualization along with working on real world use-cases. Data Science is an essential skill for analyzing and deriving useful insights from data, big and small. McKinsey estimates that by 2018, a 500,000 strong workforce of data scientists will be needed in US alone. The resulting talent gap must be filled by a new generation of data scientists.

According to, the average annual salary of a Data Scientist in the U.S. is $117,000.

All Courses of this Track


Machine Learning, Data Science

Machine Learning Foundations: Supervised Learning

Peter Chen

Practical Approach to Supervised Machine Learning


Big Data, Machine Learning, Data Science

Scaling Advanced Analytics

Sofiane Mesbah

An In-depth Advanced Analytics Training using SAS.


Operations Analytics , Big Data, Machine Learning, Executive Track, Data Science, Internet of Things

IIoT Applications for Machine Learning

Karla Yale, Randy Barnes

Learn the elements of a robust IIoT control system through applications.


Data Science

Clustering and Association Rule Mining

Anirban Ghosh

Learn Clustering methods and Association Rule Mining Techniques


Industry Track (Healthcare & Life Sciences), Machine Learning, Data Science

Machine Learning Assisted Clinical Medicine

Damiano Fantini

Analyze Clinical and Biomedical Data Using R and Data Mining / Machine Learning


Data Science

Econometric Analysis: Methods and Applications

Alan Yang

Quantitative and Econometric Analysis focused on Practical Applications


Machine Learning, Data Science

Object Oriented Python/Performance Optimization

David Sanchez

Learn object oriented design patterns and strategies for optimizing performance.


Data Science

Classification Models

Saed Sayad

How to use classification algorithms to solve real world problems.


Data Analyst, Data Science

An Introduction to R for Data Science

Kirill Eremenko, Leonid G, Laura Bolanos

Learn Programming In R And R-Studio. Data Science, Packages, Functions, GGPlot2.


Data Science

Designing & Building Business Ontologies

Dave McComb, Dan Carey, Michael Uschold

Learn to create semantic models for enterprise class applications.


Industry Track (Healthcare & Life Sciences), Data Analyst, Data Science

Predictive Analytics for Personalized Treatment Plans

Dr. Carol Hargreaves

'Prescribing the Right Treatment to the Right Patient at the Right Time'


Industry Track (Healthcare & Life Sciences), Big Data, Data Analyst, Data Science

Introduction to Healthcare Analytics

Dr. Ann E.K. Um

Healthcare Analytics: Concepts, Definitions, Technologies, and Implementations


Big Data, Machine Learning, Data Analyst, Business Intelligence, Data Science

Data Wrangling in R

Dr. Connie Brett

Real-world data preparation for further analysis using R


Big Data, Machine Learning, Data Science

Predicting Sports Outcomes Using Python and Machine Learning

Dr. Stylianos Kampakis

Sports betting and web crawling using Python and machine learning


Data Science

Probability and Statistics for Data Science with R

Kaitlin Hagan, Michael Parzen

From Basic to Advanced Applied Statistics using R


Machine Learning, Data Analyst, Executive Track, Data Science

Machine Learning for Predictive Analytics

Dr. Larry Bookman

How your organization can benefit from machine learning and predictive analytics


Operations Analytics , Big Data, Machine Learning, Data Analyst, Executive Track, Data Science, Internet of Things

Robotics Application Machine Learning

Karla Yale, Randy Barnes

Obtain the real time data exchange from the robot sensors for training AI.


Big Data, Machine Learning, Text Analytics and NLP, Data Analyst, Data Science, Web Development

Introduction to Python

Veysel Kocaman

Learn the most popular programming language of Data Science community

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