Anomaly Detection

Anomaly Detection

This course is recognized by the Operations Research Society (INFORMS) as useful preparation for the Certified Analytics Professional (CAP) exam. Complete info below to test your CAP readiness with a practice exam from INFORMS.
 
 
 
 

Aim of Course:
In this online course, you will learn how to examine data with the goal of detecting anomalies or abnormal instances. This task is critical in a wide range of applications ranging from fraud detection to surveillance. At the end of this course you will have understood the different aspects that affect how this problem can be formulated, the techniques applicable for each formulation and knowledge of some real-world applications in which they are most effective.
This course may be taken individually (one-off) or as part of a certificate program.
Course Program:

WEEK 1: Getting started

  • The different aspects of anomalies
  • Classification-based approaches

WEEK 2: Unsupervised approaches

  • Clustering
  • Nearest-neighbour
  • Other statistical techniques

WEEK 3: Non-standard approaches

  • Information-theoretic methods
  • Spectral techniques

WEEK 4: Applications

  • Credit-card fraud
  • Intrusion detection
  • Insurance
  • Healthcare
  • Surveillance
 
HOMEWORK:
Homework in this course consists of short answer questions to test concepts and guided data analysis problems using Python. There is also an end-of-the-course data analysis project.

Anomaly Detection

Who Should Take This Course:
Data scientists, business analysts, medical personnel, security specialists, statisticians, software engineers, technical managers interested in learning statistical methods to identify anomalies, appropriate techniques for handling them and the range of applications in which they occur.
Level:
Intermediate
Prerequisite:
You should have some familiarity with Python programming and command line scripting. You should be comfortable with reading technical papers from peer-reviewed journals and conferences in Artificial Intelligence.
Organization of the Course:

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.

Time Requirement:
About 15 hours per week, at times of  your choosing.

Options for Credit and Recognition:
Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:

  1. No credit - You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
  2. 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.
  3. 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.
  4. Other options - Statistics.com Specializations, INFORMS CAP recognition, and academic (college) credit are available for some Statistics.com courses

Specialization:
Specializations are an easy way for you to demonstrate mastery of a specific skill in statistics and analytics. This course is part of the Intelligence and Security Analytics Specialization which teaches statistical and machine learning methods for detecting anomalies, identifying images, and processing data from sensors. Take all three Statistics.com courses on this topic (this course, plus the courses listed to the right under "related courses," not including conferences). For savings, use the promo code "anomaly-specialization" and register for all three courses at once for $1197 ($399 per course, not combinable with other tuition savings).


INFORMS CAP:
This course is also recognized by the Institute for Operations Research and the Management Sciences (INFORMS) as helpful preparation for the Certified Analytics Professional (CAP®) exam, and can help CAP® analysts accrue Professional Development Units to maintain their certification .
Course Text:

Outlier Analysis by Charu Aggrawal. It will be supplemented by other technical papers available online.

If you want a reference for programming, Python for Data Analysis is recommended.

This course has supplemental readings that are available online.

Software:
You will use Python in this course.
Instructor(s):

Dates:

April 21, 2017 to May 19, 2017 October 20, 2017 to November 17, 2017 April 20, 2018 to May 18, 2018 October 19, 2018 to November 16, 2018

Anomaly Detection

Instructor(s):

Dates:
April 21, 2017 to May 19, 2017 October 20, 2017 to November 17, 2017 April 20, 2018 to May 18, 2018 October 19, 2018 to November 16, 2018

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.

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