This first course in the IBM Machine Learning Professional Certificate introduces you to Machine Learning and the content of the professional certificate. In this course you will realize the importance of good, quality data. You will learn common techniques to retrieve your data, clean it, apply feature engineering, and have it ready for preliminary analysis and hypothesis testing.
Exploratory Data Analysis for Machine Learning
Exploratory Data Analysis for Machine Learning
This course is part of multiple programs.
Instructors: Joseph Santarcangelo
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Gain insight into a topic and learn the fundamentals.
2,551 reviews
Intermediate level
Some related experience required
Flexible schedule
1 week at 10 hours a week
Learn at your own pace
95%
Most learners liked this course
Skills you'll gain
- Data Access
- Probability & Statistics
- Data Preprocessing
- Exploratory Data Analysis
- Data Science
- Data Analysis
- Feature Engineering
- Statistical Analysis
- Data Import/Export
- Data Manipulation
- Statistical Methods
- Data Cleansing
- Machine Learning
- Applied Machine Learning
- Statistical Inference
- Anomaly Detection
- Statistical Hypothesis Testing
Details to know
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Taught in English
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There are 5 modules in this course
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Showing 3 of 2551
KG
Reviewed on Nov 4, 2022
Good introduction to the workflow in EDA for ML. I appreciate the code examples that provide a useful reference to code syntax and some practice with EDA.
ML
Reviewed on Sep 21, 2021
Excellent, very detailed. However, if the lessons can be expand for hypothesis testing and some of their common test like T test, Anova 1 and 2 way, chi square,..it would be better further.
BD
Reviewed on Apr 23, 2024
The course includes hands-on exercises that allows us to apply the learned EDA techniques to real-world data. This practical approach helps solidify my understanding.
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