One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation.
Practical Machine Learning
Practical Machine Learning
This course is part of multiple programs.
Instructors: Jeff Leek, PhD
158,199 already enrolled
Included with Learn more
Ask Coursera
Gain insight into a topic and learn the fundamentals.
3,269 reviews
8 hours to complete
Flexible schedule
Learn at your own pace
89%
Most learners liked this course
What you'll learn
Use the basic components of building and applying prediction functions
Understand concepts such as training and tests sets, overfitting, and error rates
Describe machine learning methods such as regression or classification trees
Explain the complete process of building prediction functions
Skills you'll gain
- Model Evaluation
- Predictive Modeling
- Classification And Regression Tree (CART)
- Applied Machine Learning
- Regression Analysis
- Predictive Analytics
- Supervised Learning
- Machine Learning
- Machine Learning Methods
- Machine Learning Software
- Machine Learning Algorithms
- Model Training
- Data Preprocessing
- Random Forest Algorithm
- Feature Engineering
Tools you'll learn
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
5 assignments
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 4 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
(139 ratings)Offered by
Explore more from Machine Learning
University of Glasgow
The University of Chicago
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
66.41%
- 4 stars
22.26%
- 3 stars
6.94%
- 2 stars
2.53%
- 1 star
1.83%
Showing 3 of 3269
AC
Reviewed on May 31, 2021
A well descriptive experience for this subject; really steps into how to handle information and how to extract info from them. You need to be prepared with Regression Models, it's the base of it.
FF
Reviewed on Jul 8, 2016
Great primer for machine learning with ample additional resources for those who are interested. I feel this course gave me a solid basis to delve deeper into the topic.
UY
Reviewed on Nov 16, 2016
Great course. Only missing piece is the working information / maths behind the models. But as the name suggests it teaches practical approach towards machine learning.
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
