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Big Data Analytics

Master digital data for meaningful insights.

Big Data. Bigger Career.

Course Descriptions

To qualify for the Certificate in Big Data Analytics, students must complete all 6 courses (5 core courses + capstone project course = 18 units). A 3-year period is given for completion of the Certificate.

Core Courses (required; 15 units)

Data Analytics & Modelling
Big Data Analytics
Data Management
Predictive Modelling & Data Mining
Big Data Programming

Capstone Course (required; 3 units)

Big Data Analytics Capstone Project Course

BDA 101 Data Analytics and Modelling (3 Units)

This course offers an introduction to data science and machine learning paving the way for students to learn big data principles. In particular, this course begins with a brief history of data science, followed by regression analysis, regression and classification trees, and ends with introductions to K-means clustering, principal component analysis (PCA). Each lecture has associated with it a practical lab session which students will put "theory into practice" offering students a hands-on approach to learning the material. *Revised course description pending approval

Prerequisite: Admission to program
Instructors: Hassan Teimoori, Karim Souidi

BDA 102 Big Data Analytics (3 Units)

Building on the fundamental principles of data analytics, the course content progresses to identifying and using common analytics tools to process big data. Students will work on the identification of model structure, the processes to run, evaluate and calibrate model and data structures using applicable industry standards and software tools.

Prerequisite: BDA 101
Instructors: Omotayo Akinbode

BDA 103 Data Management (3 Units)

The course explores the importance of data management in term of the acquisition, storage, sharing, validation and accessibility of data for solving a business problem. An examination of Database Management Systems, database architectures, and the administrative processes that guide the data life cycle will be a focus of the course.

Prerequisite: BDA 101
Instructors: Guido DiCesare, Eleanor Smith

BDA 104 Predictive Modelling and Data Mining (3 Units)

The course will introduce predictive modelling techniques as well as related statistical and visualization tools for data mining. The course will cover common machine learning techniques that are focused on predictive outcomes. Students will learn how to evaluate the performance of the prediction models and how to improve them through time.

Prerequisite: BDA 101
Instructors: Haitham Amar

BDA 105 Big Data Programming (3 Units)

Developing solutions for extracting and analysing big data sets using Hadoop and Spark is the focus of the course. Students will build upon the knowledge and skills of earlier program courses to analyze large-scale network data and to problem solve potential solutions.

Prerequisite: BDA 101, BDA 102
Instructors: Yanina Shevchenko

BDA 106 Big Data Analytics Capstone Course (3 Units)

The course provides students with a real-world business problem/project in order to apply analytics models, methodologies and tools learned in the program. Faculty mentors will work with students to ensure the capstone project reflects, and encompasses, best practices for big data analytics and project management.

Prerequisite: BDA 103, BDA 104, BDA 105, or permission of Program Manager
Instructors: Jim Green

Students wishing to take multiple courses in one term should follow this learning plan:

BDA 101 and BDA 103 may be taken in the same term
BDA 102 and BDA 104 may be taken in the same term
Permission may be given to begin BDA 106 concurrently with BDA 105

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