Overview
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 Practical Machine Learning Course offered by Coursera in partnership Johns Hopkins University 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.
What you will learn
- Describe machine learning methods such as regression or classification trees
- Explain the complete process of building prediction functions
- Understand concepts such as training and tests sets, overfitting, and error rates
- Use the basic components of building and applying prediction functions
Get more details
Visit programme websiteProgramme Structure
Courses include:
- Prediction, Errors, and Cross Validation
- The Caret Package
- Predicting with trees, Random Forests, & Model Based Predictions
- Regularized Regression and Combining Predictors
Details on Coursera Plus:
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Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 1 months
Start dates & application deadlines
Language
Delivered
- Self-paced
Disciplines
Data Science & Big Data Machine Learning View 236 other Short Courses in Machine Learning in United StatesExplore more key information
Visit programme websiteAcademic 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.
Make sure you meet all requirements
Visit programme websiteTuition Fee
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 months. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 months.
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Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.