
Predictive Modelling and Data Mining - Winter 2024
DAT 203
This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. The course will introduce predictive modeling 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.

Data Analytics and Modelling - Winter 2024
DAT 201
This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. This course offers an introduction to data science and machine learning paving the way for students to learn data analytics principles. In particular, this course begins with a brief history of data analytics and 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 in which students will put "theory into practice" offering students a hands-on approach to learning the material.

Data Analysis and Visualization - Winter 2024
DAT 104
This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. The students learn how to perform exploration of data in order to discover meaningful information to solve problems, and will allow for the application of analytics life cycle in the context of planning to solve a business problem. Emphasis is placed on framing the problem, proposing an analytics solution, communicating with stakeholders, and establishing an analytics-focused project plan. Common data visualization tools and techniques are explored and used as students learn best practices for the presentation and communication of analytical solutions and insights.

Business Intelligence & Data Analytics - Winter 2024
DAT 103
This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. The course explains how to apply data analytics skills to the area of business intelligence (BI). Focus is placed on the components of the business intelligence project lifecycle such as project planning, BI tool selection, data modeling, ETL design, BI application design and deployment and reporting. The project(s) will allow the students to apply BI practices and analysis.

Statistics for Data Analysis Project - Winter 2024
DAT 101
The course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. This course introduces descriptive statistics, basic inferential statistics, linear regression, and probability concepts and calculations. Practical application activities in the course focus on how statistical methods are used in the analysis of data. Common statistical and programming tools will be introduced and employed in order to demonstrate how significant and insightful information is collected, used, and applied to problem-solving processes.

Statistical Analysis for Health Data
HDA 102
This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. This course provides a foundation to explore health data through computing and statistical analysis. Focus is placed on the structure and applications of probability, statistics, computer simulation and data analysis as applied to various types of health data. In particular, students will investigate descriptive statistics, inferential statistics, linear regression and probability concepts, hypothesis testing and foundational statistical tools are applicable to data analysis. Common statistical and programming tools will be used. Students should have an introductory/basic understanding of statistics for this course.

Predictive Modeling and Data Mining - F23
DAT 203
This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. The course will introduce predictive modeling 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.

Statistical Analysis for Data Science - F23
DAT 200
This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. This course provides a foundation of exploring data through computing and statistical analysis. Focus is placed on the structure and applications of probability, statistics, computer simulation, and data analysis for students exploring the field of data science. This course builds upon introductory statistics courses and is designed for students with experience/study in programming, calculus, and algebra. Programming in R will be used throughout the course.

Data Analysis and Visualization - F23
DAT 104
This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. The students learn how to perform exploration of data in order to discover meaningful information to solve problems, and will allow for the application of analytics life cycle in the context of planning to solve a business problem. Emphasis is placed on framing the problem, proposing an analytics solution, communicating with stakeholders, and establishing an analytics-focused project plan. Common data visualization tools and techniques are explored and used as students learn best practices for the presentation and communication of analytical solutions and insights.

Data Science Capstone Project - F23
DAT 205
The capstone course is part of the Big Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. Students apply analytical models, methodologies, and tools learned in the program to create an analytics solution for your organization. Faculty mentors will work with students to ensure the capstone project reflects, and encompasses, best practices for big data analytics and project management.

Data Analytics and Modelling - F23
DAT 201
This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. This course offers an introduction to data science and machine learning paving the way for students to learn data analytics principles. In particular, this course begins with a brief history of data analytics and 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 in which students will put "theory into practice" offering students a hands-on approach to learning the material.

Business Intelligence & Data Analytics - F23
DAT 103
This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. The course explains how to apply data analytics skills to the area of business intelligence (BI). Focus is placed on the components of the business intelligence project lifecycle such as project planning, BI tool selection, data modeling, ETL design, BI application design and deployment and reporting. The project(s) will allow the students to apply BI practices and analysis.

Data Analytics and Modelling
DAT 201
This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. This course offers an introduction to data science and machine learning paving the way for students to learn data analytics principles. In particular, this course begins with a brief history of data analytics and 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 in which students will put "theory into practice" offering students a hands-on approach to learning the material.

Business Intelligence & Data Analytics
DAT 103
This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. The course explains how to apply data analytics skills to the area of business intelligence (BI). Focus is placed on the components of the business intelligence project lifecycle such as project planning, BI tool selection, data modeling, ETL design, BI application design and deployment and reporting. The project(s) will allow the students to apply BI practices and analysis.

Statistics for Data Analysis Project
DAT 101
The course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. This course introduces descriptive statistics, basic inferential statistics, linear regression, and probability concepts and calculations. Practical application activities in the course focus on how statistical methods are used in the analysis of data. Common statistical and programming tools will be introduced and employed in order to demonstrate how significant and insightful information is collected, used, and applied to problem-solving processes.

Big Data Programming and Architecture Capstone
DAT 305
This course covers advanced-level topics in the areas of data science, machine learning, and technical/software applications. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. They will practice their knowledge of using various technologies as part of the course, such as real-time analytics tools (e.g., Kafka and HBase), NoSQL databases, and cloud technologies. Students will apply analytical models, methodologies, and tools learned in the program to create an analytics solution for your organization, with support from faculty mentors, who will work with students.

Data Science Capstone Project
DAT 205
The capstone course is part of the Big Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. Students apply analytical models, methodologies, and tools learned in the program to create an analytics solution for your organization. Faculty mentors will work with students to ensure the capstone project reflects, and encompasses, best practices for big data analytics and project management.

Big Data Programming and Architecture Capstone
DAT 305
This course covers advanced-level topics in the areas of data science, machine learning, and technical/software applications. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. They will practice their knowledge of using various technologies as part of the course, such as real-time analytics tools (e.g., Kafka and HBase), NoSQL databases, and cloud technologies. Students will apply analytical models, methodologies, and tools learned in the program to create an analytics solution for your organization, with support from faculty mentors, who will work with students.

Data Science Capstone Project
DAT 205
The capstone course is part of the Big Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. Students apply analytical models, methodologies, and tools learned in the program to create an analytics solution for your organization. Faculty mentors will work with students to ensure the capstone project reflects, and encompasses, best practices for big data analytics and project management.

Big Data Programming and Architecture Capstone
DAT 305
This course covers advanced-level topics in the areas of data science, machine learning, and technical/software applications. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. They will practice their knowledge of using various technologies as part of the course, such as real-time analytics tools (e.g., Kafka and HBase), NoSQL databases, and cloud technologies. Students will apply analytical models, methodologies, and tools learned in the program to create an analytics solution for your organization, with support from faculty mentors, who will work with students.

Data Science Capstone Project
DAT 205
The capstone course is part of the Big Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. Students apply analytical models, methodologies, and tools learned in the program to create an analytics solution for your organization. Faculty mentors will work with students to ensure the capstone project reflects, and encompasses, best practices for big data analytics and project management.

Data Science Capstone Project
DAT 205
The capstone course is part of the Big Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. Students apply analytical models, methodologies, and tools learned in the program to create an analytics solution for your organization. Faculty mentors will work with students to ensure the capstone project reflects, and encompasses, best practices for big data analytics and project management.

Big Data Programming and Architecture Capstone
DAT 305
This course covers advanced-level topics in the areas of data science, machine learning, and technical/software applications. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. They will practice their knowledge of using various technologies as part of the course, such as real-time analytics tools (e.g., Kafka and HBase), NoSQL databases, and cloud technologies. Students will apply analytical models, methodologies, and tools learned in the program to create an analytics solution for your organization, with support from faculty mentors, who will work with students.

Data Science Capstone Project
DAT 205
The capstone course is part of the Big Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. Students apply analytical models, methodologies, and tools learned in the program to create an analytics solution for your organization. Faculty mentors will work with students to ensure the capstone project reflects, and encompasses, best practices for big data analytics and project management.

Data Science Capstone Project
DAT 205
The capstone course is part of the Big Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. Students apply analytical models, methodologies, and tools learned in the program to create an analytics solution for your organization. Faculty mentors will work with students to ensure the capstone project reflects, and encompasses, best practices for big data analytics and project management.

Big Data Analytics Capstone
BDA 106
The capstone course is part of the Big Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. Students apply analytical models, methodologies, and tools learned in the program to create an analytics solution for your organization. Faculty mentors will work with students to ensure the capstone project reflects, and encompasses, best practices for big data analytics and project management.