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NOTE: Course offerings are subject to budgetary approval
Posting Reference: TME 6014 FR01A
| Course Prefix: | TME | Course Number: | 6014 |
| Course Section: | FR01A | Course Name: | Data Analytics |
| Term: | Fall | Campus: | Fredericton |
| Faculty: | Engineering, Faculty of | Department: | Technology Management and Entrepreneurship |
| Position Start Date: | 2025-09-09 | Position End Date: | 2025-12-31 |
| Posting Date: | 2025-05-30 | Application Deadline: | 2025-06-13 |
| Applications to be submitted via: | henry.brookebrunsdon@unb.ca | ||
| Requested By: | Dr. Dhirendra Shukla |
| Days: | T | Time: | 5:00 PM - 7:50 PM |
| Number of Positions Available: | 1 | Total Credit Hours: | 3 |
| Mode of Delivery: | Face to Face | Location: | On Campus |
| Stipend Amount: | $7,193.00 |
Technology Management & Entrepreneurship (TME) course
The purpose of this course topic is to familiarize broad audiences of students from science and engineering into Artificial Intelligence (AI) and Machine Learning (ML) and encourage them to design their own data science workflow for a given real-life application. Students will learn how different data structures and data types are generated and handled from different acquisition modalities for the purpose of AI/ML development. Formats of continuous versus discrete data will be discussed in multi-dimensional structure. Different applications in real-world examples will be introduced such as in engineering, medicine, and science. Techniques of pre-processing for cleansing the data and their preparation will be introduced. Data management systems will be discussed and explained how to handle big data storage and communication. Post-processing techniques such as QA measures, enhancements methods, augmentation, dimensionality reduction, visualization of data for locally vs globally distributed data will be discussed.
Applicants should include the following with their application: