Data Science Ready from Harvard Online

Data Science Ready is a Harvard Online course in collaboration with Harvard Business School Online that allows you to gain a familiarity with the fundamental concepts and use of data science, including prediction, causality, data wrangling, privacy, and ethics.
Apply NowWhat You'll Learn
- Understand the modern data science landscape and technical terminology for a data-driven world
- Recognize major concepts and tools in the field of data science and determine where they can be appropriately applied
- Appreciate the importance of curating, organizing, and wrangling data
- Explain uncertainty, causality, and data quality—and the ways they relate to each other
- Predict the consequences of data use and misuse and know when more data may be needed or when to change approaches
About the Professor

Dustin Tingley is Deputy Vice Provost for Advances in Learning, Faculty Director for the Vice Provost for Advances in Learning Research Group, Faculty Director for the Harvard Initiative on Learning and Teaching, and Professor of Government in the Government Department at Harvard University. His research interests include international relations, international political economy, statistical methodology, and experimental approaches to political science. Recent projects include attitudes towards global climate technologies and policies, and the intersection of causal inference and machine learning methods for the social sciences.
Who Will Benefit
Organizational
Leaders
Recognize how data science is changing your industry and think critically about how to apply these new learnings to your workplace.
Managers
Prepare to speak the language of data science and contribute to data-oriented discussions within your company.
Business Operations
Specialists
Gain a fundamental understanding of the essential concepts, vocabulary, skills, and intuition necessary for data visualization basics.
Program Structure
Data Science Ready consists of approximately 15 hours of material delivered over a four-week period. You can complete the coursework on your own time while meeting regular deadlines.
- Length: 4 Weeks
- Program Dates: 1/27/21 – 2/24/21
- Cost: $1,600
- Application Deadline: January 14
- Detailed Calendar
- Length: 4 Weeks
- Program Dates: 4/14/21 – 5/12/21
- Cost: $1,600
- Application Deadline: April 5
- Detailed Calendar
Syllabus
Data Science Ready makes the fundamental topics in data science approachable and relevant by using real-world examples and prompts learners to think critically about applying these new understandings to their own workplace. Get an overview of data science with a code- and math-free introduction to prediction, causality, visualization, data wrangling, privacy, and ethics.
Learning requirements: In order to earn a Certificate of Completion from Harvard Online and Harvard Business School Online, participants must thoughtfully complete all 7 modules, including satisfactory completion of associated quizzes, by stated deadlines.
Modules | Case Studies | Takeaways | Key Exercises |
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Module 1: Data 101 |
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Module 2: Predictions and Recommendations |
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Module 3: Cause and Effect |
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Module 4: Data Governance and Privacy |
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Module 5: Beyond the Spreadsheet |
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Module 6: Data Science Ecosystems |
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Module 7: The Road Ahead |
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The HBS Online Advantage
- World-class faculty
- Edge-of-your-seat online learning
- Global peer collaboration and networking
- Real-world, case-based learning
Harvard Business School Online offers a unique and highly engaging way to learn vital business concepts. Immerse yourself in real challenges faced by business leaders across a variety of industries. You’ll wrestle with the same issues and imperfect information, while problem-solving and interacting with fellow learners from around the world.
Stories from Our Learners
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The platform was engaging, innovative, and allowed me to interact with the material in a way I never expected from an online course.
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I had never experienced such an immersive platform online, and could argue that it was more effective at building and solidifying knowledge than some of the in-class courses I took in college.
