Data Mining in R
taught by Inbal Yahav
In this online course, “Data Mining in R,” you will learn how to partition data and use a holdout sample, how to measure the performance of predictive models, and what to do about the problem of overfitting. Popular classification methods (logistic regression, k-nearest-neighbors, classification trees) and prediction methods (linear regression and regression trees) are discussed. Collaborative filtering and association rules are also covered.
WEEK 1: Getting Started
- Data prep
- Data partitioning (holdout data)
- Measuring the performance of classification and prediction models
- K-nearest neighbors classification
WEEK 2: Linear Regression and CART
- Multiple linear regression
- Classification and regression trees
WEEK 3: Logistic Regression
- Propensities and ranking
WEEK 4: Recommender Systems
- Association Rules - Apriori Algorithm
- Collaborative Filtering - k-Nearest neighbors
Homework in this course consists of short answer questions to test concepts and guided data analysis problems using software.
Data Mining - R
R users who want to learn how to apply R to data mining. Data mining analysts in search of new tools. Students in statistics.com's PASS program in Data Mining seeking an affordable data mining tool. Note that working in R will be more involved than using a specially designed interface for data mining, such as those found in major commercial data mining programs.
1+ years of programming using R, or
R Programming Introduction 1 and R Programming Introduction 2
plus 1+ years using R or another programming language.
This course takes place online at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.
At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.
About 15 hours per week, at times of your choosing.
Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:
- No credit - You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
- Certificate - You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
- CEUs and/or proof of completion - You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's). For those successfully completing the course, CEU's and a record of course completion will be issued by The Institute, upon request.
- Other options - Statistics.com Specializations, INFORMS CAP recognition, and academic (college) credit are available for some Statistics.com courses
All required study materials will be provided in the course.
You must have a copy of R for the course. Click here for information on obtaining a free copy. After installing R in your computer you must also install several R add-on packages. Instructions for this installation will be provided as needed.
To be scheduled.
Data Mining - R
To be scheduled.
Course Fee: $549
Do you meet course prerequisites? What about book & software? (Click here to learn more)
We have flexible policies to transfer to another course, or withdraw if necessary (modest fee applies)
Group rates: Click here to get information on group rates.
First time student or academic? Click here for an introductory offer on select courses. Academic affiliation? You may be eligible for a discount at checkout.
Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment. Please use this printed registration form, for these and other special orders.
Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise.
The Institute for Statistics Education is certified to operate by the State Council of Higher Education in Virginia (SCHEV).
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