Overview
Join over 9 million learners and start Dealing with Missing Data in Python today!
Tired of working with messy data? Did you know that most of a data scientist's time is spent in finding, cleaning and reorganizing data?! Well turns out you can clean your data in a smart way! In this Dealing with Missing Data in Python course at Data Camp, you'll do just that! You'll learn to address missing values for numerical, and categorical data as well as time-series data. You'll learn to see the patterns the missing data exhibits! While working with air quality and diabetes data, you'll also learn to analyze, impute and evaluate the effects of imputing the data.
Programme Structure
Chapters include:
- The Problem With Missing Data
- Imputation Techniques
- Does Missingness Have A Pattern?
- Advanced Imputation Techniques
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
Data Science & Big Data Software Engineering View 550 other Short Courses in Software Engineering 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
- Supervised Learning with scikit-learn
- Introduction to Data Visualization with Matplotlib
- Data Manipulation with pandas
Tuition Fee
To always see correct tuition fees
-
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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