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
Ends in 6 days! Save 40% on your access to 10,000+ programs and make a real impact in your career. Save now.
Exploratory Data Analysis for Machine Learning
This course is part of multiple programs.
Instructors: Joseph Santarcangelo
196,790 already enrolled
Included with Learn more
Ask Coursera
Gain insight into a topic and learn the fundamentals.
2,584 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
- Statistical Methods
- Statistics
- Data Processing
- Exploratory Data Analysis
- Probability & Statistics
- Statistical Analysis
- Data Science
- Data Manipulation
- Data Import/Export
- Data Access
- Feature Engineering
- Statistical Inference
- Applied Machine Learning
- Data Analysis
- Data Preprocessing
- Data Wrangling
- Machine Learning
- Data Transformation
- Data Cleansing
- Statistical Hypothesis Testing
Details to know
Shareable certificate
Add to your LinkedIn profile
Taught in English
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
This course is available as part of
When you enroll in this course, you'll also be asked to select a specific program.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
There are 5 modules in this course
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Instructors
Instructor ratings
(798 ratings)Offered by
Explore more from Machine Learning
Status: Top AI Program
Status: Free Trial
Status: Free Trial
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Learner reviews
- 5 stars
73.02%
- 4 stars
19.15%
- 3 stars
4.48%
- 2 stars
1.81%
- 1 star
1.50%
Showing 3 of 2584
OS
Reviewed on Jul 1, 2023
Well explained concepts and spoke at the right speed. But, some of the hypothesis testing, probability, and Bayesian statistics material could've been explained better with more visuals perhaps.
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.
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.
¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.