Data Science Specialization
Launch Your Career in Data Science. A nine-course introduction to data science, developed and taught by leading professors.
Data Science Specialization
10 coursesWhat 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
Skills you will gain
Syllabus - What you will learn from this course
1
Week 1: Prediction, Errors, and Cross Validation
2
Week 2: The Caret Package
3
Week 3: Predicting with trees, Random Forests, & Model Based Predictions
4
Week 4: Regularized Regression and Combining Predictors
34%
83%
14%
Top Reviews
excellent course. Be prepared to learn a lot if you work hard and don't give up if you think it is hard, just continue thinking, and interact with other students and tutors + Google and Stackoverflow!
Issues of every stage of the construction of learning machine model, as well as issues with several different machine learning methods are well and in fine yet very understandable detail explained.
Instructors
Jeff Leek, PhD
Associate Professor, Biostatistics
Roger D. Peng, PhD
Associate Professor, Biostatistics
Brian Caffo, PhD
Professor, BiostatisticsAbout Johns Hopkins University
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I pay for this course?
If you pay for this course, you will have access to all of the features and content you need to earn a Course Certificate. If you complete the course successfully, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. Note that the Course Certificate does not represent official academic credit from the partner institution offering the course.
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