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Hamilton, Ontario, Canada
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Big Data Programming and Architecture Capstone - Winter 2024
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.

Essentials of Cloud Computing - Winter 2024
DAT 304
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. Students will explore the principles and practices of cloud computing with this introductory course, and discover the importance of cloud computing for today’s business and IT sectors through an examination of the development of cloud technologies over time. Common practices for delivery, deployment, architecture and security will be presented. Students will explore various cloud computing platforms to understand and assess current service options and to discuss future developments for cloud computing -- The project provides an opportunity for businesses and learners to collaborate to identify and translate a real business problem into an analytics problem. The projects, which can be short, will allow the student to apply the skills acquired on to address the business problem. Some examples are: Determine the characteristics of the collection system and select a collection system that handles the large data set Identify the right storage solution for analytics Design and implement a solution for transforming and preparing data for analysis Select the right data analysis and data visualization solution for a given scenario Apply the right authentication and authorization mechanisms Apply data protection and encryption techniques Manage and monitor data solutions You should submit a high-level proposal/business problem statement including relevant data sets and definitions, a list of acceptable tools (if applicable), and expected deliverables. Business datasets could be provided based on a non-disclosure agreement or in an anonymized/synthetic data format that is relevant to your organization and business problem. The course instructors will review the documents to confirm the scope and timing of the proposed problem and its alignment with the course requirements.

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.

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.