BAN210 - Predictive Analytics

Outline information
Semester
Schools offering this subject
Last revision date 2023-10-02 01:50:26.663
Last review date 2023-12-04 00:15:16.235

Subject Title
Predictive Analytics

Subject Description

This course will introduce students to recent developments in advanced analytics techniques.  Predictive analytics encompasses a variety of machine learning techniques that analyse current and historical facts to make predictions about unknown future events.  In this course, students will learn how to build a predictor through supervised or unsupervised techniques in a training stage, and will evaluate the predictor performance through a tester stage.

?

Credit Status
1 credit toward the Business Analytics Graduate Certificate program

Learning Outcomes
Upon successful completion of this subject the student will be able to:

Upon successful completion of this subject the student will be able to:
 
  1. Describe how predictive modeling expresses the relationship between an outcome variable and a set of input variables
  2. Discuss the risks and ethics of predictive analytics
  3. Select an evaluation methodology to assess the predictor accuracy based on randomly sampled partitions of the given data
  4. Determine the bias-variance tradeoff in overfitting vs. underfitting of models
  5. Use unsupervised models for descriptive modelling
  6. Predict a continuous and/or categorical response using straight-line and polynomial regression functions given a single or multiple predictor variables.
  7. Use a classification model to predict a target label of a data point.
  8. Use probability-based methods to predict a continuous or categorical response.
  9. Apply time series algorithms to predict the value of the target variable for a future timeframe given historical values.
  10. Discuss ensemble methods to combine models together for higher performance.

Academic Integrity
Seneca upholds a learning community that values academic integrity, honesty, fairness, trust, respect, responsibility and courage. These values enhance Seneca's commitment to deliver high-quality education and teaching excellence, while supporting a positive learning environment. Ensure that you are aware of Seneca's Academic Integrity Policy which can be found at: http://www.senecapolytechnic.ca/about/policies/academic-integrity-policy.html Review section 2 of the policy for details regarding approaches to supporting integrity. Section 2.3 and Appendix B of the policy describe various sanctions that can be applied, if there is suspected academic misconduct (e.g., contract cheating, cheating, falsification, impersonation or plagiarism).

Please visit the Academic Integrity website http://open2.senecac.on.ca/sites/academic-integrity/for-students to understand and learn more about how to prepare and submit work so that it supports academic integrity, and to avoid academic misconduct.

Discrimination/Harassment
All students and employees have the right to study and work in an environment that is free from discrimination and/or harassment. Language or activities that defeat this objective violate the College Policy on Discrimination/Harassment and shall not be tolerated. Information and assistance are available from the Student Conduct Office at student.conduct@senecapolytechnic.ca.

Accommodation for Students with Disabilities
The College will provide reasonable accommodation to students with disabilities in order to promote academic success. If you require accommodation, contact the Counselling and Accessibility Services Office at ext. 22900 to initiate the process for documenting, assessing and implementing your individual accommodation needs.

Camera Use and Recordings - Synchronous (Live) Classes
Synchronous (live) classes may be delivered in person, in a Flexible Learning space, or online through a Seneca web conferencing platform such as MS Teams or Zoom. Flexible Learning spaces are equipped with cameras, microphones, monitors and speakers that capture and stream instructor and student interactions, providing an in-person experience for students choosing to study online.

Students joining a live class online may be required to have a working camera in order to participate, or for certain activities (e.g. group work, assessments), and high-speed broadband access (e.g. Cable, DSL) is highly recommended. In the event students encounter circumstances that impact their ability to join the platform with their camera on, they should reach out to the professor to discuss. Live classes may be recorded and made available to students to support access to course content and promote student learning and success.

By attending live classes, students are consenting to the collection and use of their personal information for the purposes of administering the class and associated coursework. To learn more about Seneca's privacy practices, visit Privacy Notice.