Artificial Intelligence & Data Science
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Professional Certificate in Data Science

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Course Features

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Duration

17 months

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Beginner

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Effort

3 hours per week

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Teaching Type

Self Paced

Course Description

There is a growing demand for data scientists in government, academia, industry and other sectors. The HarvardX Data Science program equips you with the knowledge and skills necessary to solve real-world data analysis problems. This program covers topics such as probability and inference and machine learning. It also helps you to develop essential skills like R programming, data wrangling using dplyr and data visualization with ggplot2. File organization with Unix/Linux is also included. Version control with git or GitHub is also available. You can also prepare reproducible documents with RStudio.

Each course uses motivating case studies and asks specific questions. Then, we learn through data analysis. These case studies include: Trends in World Health and Economics; US Crime Rates; The Financial Crisis of 2007–2008; Election Forecasting; Building a Baseball Team (inspire by Moneyball); and Movie Recommendation Systems.

We will use R throughout the program. R, statistical concepts and data analysis techniques will all be covered simultaneously. It is our belief that it is easier to retain R knowledge if you are able to solve specific problems.

Course Overview

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International Faculty

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Case Based Learning

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Post Course Interactions

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Case Studies,Instructor-Moderated Discussions

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Case Studies, Captstone Projects

Skills You Will Gain

Prerequisites/Requirements

There are no prerequisites for the first course, but the later courses assume knowledge from the prior courses in the series

What You Will Learn

Fundamental R programming skills

Statistical concepts such as probability, inference, and modeling and how to apply them in practice

Gain experience with the tidyverse, including data visualization with ggplot2 and data wrangling with dplyr

Become familiar with essential tools for practicing data scientists such as Unix/Linux, git and GitHub, and RStudio

Implement machine learning algorithms

In-depth knowledge of fundamental data science concepts through motivating real-world case studies

Course Instructors

Rafael Irizarry

Professor of Biostatistics

Rafael Irizarry is a Professor of Biostatistics at the Harvard T.H. Chan School of Public Health and a Professor of Biostatistics and Computational Biology at the Dana Farber Cancer Institute. For th...
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