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Data Science Ready from Harvard Online

Data Science Ready from Harvard Online
Man analyzing data visualizations on an ipad
Data Science Ready from Harvard Online
Prepare for a Data-Driven World

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.

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What You'll Learn

Play an Introduction to Data Science Ready video
Play an Introduction to Data Science Ready video
Go to Course Syllabus
  • 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

Professor Dustin Tingley - Data Science Ready

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

Group

Organizational
Leaders

Recognize how data science is changing your industry and think critically about how to apply these new learnings to your workplace.

Pitch

Managers

Prepare to speak the language of data science and contribute to data-oriented discussions within your company.

Briefcase

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.

January 2021
  • Length: 4 Weeks
  • Program Dates: 1/27/21 – 2/24/21
  • Cost: $1,600
  • Application Deadline: January 14
  • Detailed Calendar
  • Course Platform
  • Certificate Program
Apply Now
April 2021
  • Length: 4 Weeks
  • Program Dates: 4/14/21 – 5/12/21
  • Cost: $1,600
  • Application Deadline: April 5
  • Detailed Calendar
  • Course Platform
  • Certificate Program
Apply Now

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.

Download Syllabus

Modules Case Studies Takeaways Key Exercises
Module 1: Data 101
  • Flu Detection
  • Explain why data collection is important
  • Identify factors that may affect data quality
  • Recognize that not all data is numerical
  • Explain how the organization of data can affect the information you are able to extract from it
  • List sources of data
  • Discuss what can be done with data
  • Categorize data by various factors
  • Determine whether data is high-quality or not
Module 2: Predictions and Recommendations
  • Predicting Sepsis
  • Understand the basic structure of a predictive algorithm
  • Identify where human decisions shape predictive systems
  • Evaluate the success of a predictive system
  • Examine how weather forecasts work
  • Use data to create a prediction
  • Sort types of training data
  • Simulate a predictive system
Module 3: Cause and Effect
  • The Google Tax
  • Explain why it is important to establish causal relationships
  • Identify barriers to establishing causal relationships in a variety of settings
  • Identify why randomization can help establish a causal relationship but also create other problems
  • Classify relationships based on correlation or causation
  • Examine the relationship between variables
  • Identify potential common causes for correlated events
Module 4: Data Governance and Privacy
  • Privacy and Facial Recognition
  • Explain why data privacy is important
  • Describe what can constitute a violation of privacy
  • Critique existing privacy policies
  • Create a set of ethical tenets to guide data work at their own organizations
  • Formulate data privacy guidelines
  • Discuss the risks of data re-identification
  • Evaluate existing data privacy policies for ethics
Module 5: Beyond the Spreadsheet
  • Burning Glass and Text Data
  • Identify sources of non-numerical data
  • Explain why it would be useful to use non-numerical data
  • Describe the differences in approach for supervised and unsupervised learning
  • Identify use cases for neural networks
  • Perform a sentiment analysis
  • Determine what types of data an algorithm cannot read
  • Examine how computers intake visual and audio data
  • Experiment with facial recognition
Module 6: Data Science Ecosystems
  • Harvard Link
  • Explain the importance of data transformation and wrangling
  • List the common technologies used within data science ecosystems
  • Describe the connection between data science tasks, software tools, and hardware tools
  • Identify potential sources of bottlenecks in the data science process
  • Identify and order the lifecycle of data
  • Define what "the cloud" is
  • Estimate the size of various data streams
Module 7: The Road Ahead
  • N/A
  • Recognize a problem that an algorithm might be able to solve
  • Recognize the challenges created by using data science tools in ways outside their intended use
  • Identify steps within the data science process that need auditing
  • Choose types of data to ingest into an algorithm
  • Evaluate the risks of soley using an algorithm to make decisions
  • Discuss how algorithms can reinforce biases
  • Create a set of guidelines to evaluate projects

The HBS Online Advantage

Play an Introduction to the HBS Online Platform video
Play an Introduction to the HBS Online Platform video
  • 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.

Play students explain their experience an HBS Online course video
Play students explain their experience an HBS Online course video

Stories from Our Learners

  • The platform was engaging, innovative, and allowed me to interact with the material in a way I never expected from an online course.
    Bethany Larson,
    HBS Online Participant
  • 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.
    Ryan Dumlao,
    HBS Online Participant


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Frequently Asked Questions

Do I have to log in at a set time? How does the grading process work? At this point, you probably have a few questions, and we’ve got answers.

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Enrollment Eligibility

Our easy online application is free, and no special documentation is required. All applicants must be at least 18 years of age, proficient in English, and committed to learning and engaging with fellow participants throughout the course. We confirm enrollment eligibility within one week of your application.

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Data Science Ready Certificate of Completion from HBS Online
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Enroll today in Harvard Online's Data Science Ready course.

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  • Disruptive Strategy
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  • Global Business
  • Leadership Principles
  • Leading with Finance
  • Management Essentials
  • Negotiation Mastery
  • Sustainable Business Strategy

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Sign up for News & Announcements

News

  • How to Prepare Financially for an Economic Recession
  • Mini-courses pave the way to a full MBA
  • New Dean of Harvard Business School Online Aims for Modular Courses, More Diversity
  • HBS Online Will Keep Changing The Game. Here’s How.

Courses

  • CORe
  • Alternative Investments
  • Business Analytics
  • Data Science Ready
  • Disruptive Strategy
  • Economics for Managers
  • Entrepreneurship Essentials
  • Financial Accounting
  • Global Business
  • Leadership Principles
  • Leading with Finance
  • Management Essentials
  • Negotiation Mastery
  • Sustainable Business Strategy

Quick Links

  • Frequently Asked Questions
  • Contact Us
  • Apply Now

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