Harvard University - Data Science: Inference and Modeling
- Offered byedX
Data Science: Inference and Modeling at edX Overview
Data Science: Inference and Modeling
at edX
Learn inference and modeling, two of the most widely used statistical tools in data analysis.
Duration | 12 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Data Science: Inference and Modeling at edX Highlights
Data Science: Inference and Modeling
at edX
- Hands On Learning with peer graded assignments etc.
- Instructor -
Rafael Irizarry - Effort - 1?2 hours per week
- FREE
Add a Verified Certificate for ?3,656
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Data Science: Inference and Modeling at edX Course details
Data Science: Inference and Modeling
at edX
Skills you will learn
Who should do this course?
- This course is designed for those who want to become an expert data scientist
More about this course
- Statistical inference and modeling are indispensable for analyzing data affected by chance, and thus essential for data scientists. In this course, you will learn these key concepts through a motivating case study on election forecasting. This course will show you how inference and modeling can be applied to develop the statistical approaches that make polls an effective tool and we'll show you how to do this using R. You will learn concepts necessary to define estimates and margins of errors and learn how you can use these to make predictions relatively well and also provide an estimate of the precision of your forecast. Once you learn this you will be able to understand two concepts that are ubiquitous in data science: confidence intervals, and p-values. Then, to understand statements about the probability of a candidate winning, you will learn about Bayesian modeling. Finally, at the end of the course, we will put it all together to recreate a simplified version of an election forecast model and apply it to the 2016 election.
Data Science: Inference and Modeling at edX Curriculum
Data Science: Inference and Modeling
at edX
The concepts necessary to define estimates and margins of errors of populations, parameters, estimates and standard errors in order to make predictions about data
How to use models to aggregate data from different sources
The very basics of Bayesian statistics and predictive modeling
Data Science: Inference and Modeling at edX Admission Process
Data Science: Inference and Modeling
at edX
Important Dates
May 25, 2024
Course Commencement Date
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Data Science: Inference and Modeling
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