Overview
Context of the Handling Missing Data with Imputations in R course at Data Camp
Missing data is everywhere. The process of filling in missing values is known as imputation, and knowing how to correctly fill in missing data is an essential skill if you want to produce accurate predictions and distinguish yourself from the crowd.
You’ll also gain decision-making skills, helping you decide which imputation method fits best in a particular situation. Finally, you’ll learn to incorporate uncertainty from imputation into your inference and predictions, making them more robust and reliable.
Programme Structure
Chapters
- The problem of missing data
- Donor-based imputation
- Model-based imputation
- Uncertainty from imputation
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Disciplines
Computer Sciences Data Science & Big Data View 746 other Short Courses in Computer Sciences in United StatesAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
PREREQUISITES
- Multiple and Logistic Regression in R
- Dealing With Missing Data in R
Tuition Fee
To always see correct tuition fees
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International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days.
Basic Access: Free; Premium (for individuals): $12.42 per month billed annually; Teams: $25 per month billed annually; Enterprise: Contact sales for pricing
Funding
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