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Data Mining and Analytics COMP 8575

Computer Systems Course

International Fees

International fees are typically three times the amount of domestic fees. Exact cost will be calculated upon completion of registration.

Course details

​This course is focused on incorporating data mining and integrating data analytics frameworks to database systems, data warehouses and big data infrastructures. Approaches for mining correlations, associations and other data patterns are studied. Clustering, classification and regression implementations are integrated with the data systems. Database applications utilizing charts, maps and AR/VR augmented data visualization to support visual analytics are developed.

Prerequisite(s)

Credits

3.0

Domestic fees

$819.54

Course offerings

Spring/Summer 2024

Below is one offering of COMP 8575 for the Spring/Summer 2024 term.

CRN 68119

Duration

Thu Apr 04 - Thu Jun 20 (12 weeks)

  • 12 weeks
  • CRN 68119
  • Domestic fees $819.54
    International fees are typically three times the amount of domestic fees.
Class meeting times
Dates Days Times Locations
Apr 04 - Jun 20 Thu 18:30 - 22:15 Downtown DTC Rm. 678
Instructor

Tejinder Randhawa

Course outline

View

Domestic fees

$819.54

Important information
  1. Departmental approval needed
  2. International fees are typically three times the amount of domestic fees. Exact cost will be calculated upon completion of registration.
  3. 1. Please email compBSc@bcit.ca for departmental approval. Include your full name, student number (A0#), course number (e.g. COMP 7000), and CRN #. 2. This is a BScACS course. BScACS courses are also open to non-bachelor program students, if approval is granted by the BScACS Program Head. 3. BScACS program students have up to seven (7) years to complete the program starting from the date of their first technical degree-level course or the date of acceptance to the BScACS program, whichever comes first.
Status

In Progress

This course offering is in progress. Please check back next term or subscribe to receive email updates.

Learning Outcomes

Upon successful completion of this course, the student will be able to:

  • Apply descriptive, predictive and prescriptive analytics for business intelligence purposes.
  • Use SQL and its extensions as well as statistical functions provided natively by the underlying data warehouses and big data solutions to determine basic statistical description of data.
  • Apply data clustering and regression techniques supplied by popular off-the-shelf business intelligence solutions to conduct predictive analysis.
  • Integrate data clustering approaches such as K-Means / NN, Bayesian Classifier, Decision Tree as well as regression techniques including neural nets to the data warehouses and big data storage.
  • Implement and integrate prescriptive analytics to optimize business decisions.
  • Integrate libraries supporting plots, charts and maps with database applications to support custom visual analytics needs of business intelligence.
  • Describe data and expose any coherence, correlations and/or trends among data values through suitable visual representations for visual analytics purposes.
  • Generate 3D models and AR/VR augmented representations of data using 3D modeling tools and AR/VR platforms to evaluate efficacy of such data visualization approaches for business intelligence and decision making.

Effective as of Fall 2019

Related Programs

Data Mining and Analytics (COMP 8575) is offered as a part of the following programs:

School of Computing and Academic Studies

  1. Applied Computer Science (Database Option)
    Bachelor of Science Part-time
  2. Applied Computer Science (Human Computer Interface Option)
    Bachelor of Science Part-time
  3. Applied Computer Science (Wireless and Mobile Applications Development Option)
    Bachelor of Science Part-time

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