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Digital Innovation MDI
The Digital Innovation MDI program is offered by the Faculty of Computer Science at Dalhousie University.
Program Overview
The Certificate in Data Science provides students with the knowledge to draw conclusions on data reliably and robustly. Courses in Computer Science, Statistics, and Management will teach students to implement an array of data science/statistics methods, models, and tools in any business.
Program Structure
The program consists of four terms:
- Term 1: 2 foundation courses + 1 elective or certificate course
- Term 2: 1 required course + 2 elective or certificate courses
- Term 3: DGIN 7000: Internship (internship students) or DGIN 9000: Master's Thesis (thesis students)
- Term 4: DGIN 5001: Capstone (internship students) or DGIN 5002: Research Methods (thesis students) + 2 elective or certificate courses
Customizing Your Degree
Although all MDI students follow a required program outline, they can create their own degree with a wide variety of elective options that support the Certificate in Data Science.
Required Courses
One of the following courses is assigned by the graduate committee based on academic background and goals:
- DGIN 5100 Foundations in Web Technologies
- DGIN 5200 Foundations in Business
- DGIN 5300 Law, Policy, and Ethics in Emerging Technologies
- DGIN 5400 Statistics for Health Informatics
Core Course
- DGIN 5201 Digital Transformation
Certificate Courses
- STAT 5620 Data Analysis
- CSCI 6409 The Process of Data Science
- CSCI 6505 Machine Learning
Elective Courses
Students can choose two elective courses from the following:
- BUSI/INFO 6513 Business Analytics and Data Visualization
- INFO 6681 Geospatial Information Management
- STAT 5130 Bayesian Data Analysis
- STAT 5350 Applied Multivariate Analysis
- STAT 5390 Time Series Analysis
- STAT 5550 Longitudinal Data Analysis
- CSCI 6405 Data Mining and Data Warehousing
- CSCI 6406 Visualization
- CSCI 6509 Advanced Topics in Natural Language Processing
- CSCI 6515 Machine Learning for Big Data
- CSCI 6612 Visual Analytics
- DGIN 5401 Operationalized Machine Learning in Healthcare
Course Descriptions
DGIN 5100 Foundations in Web Technologies
This hands-on course examines the technologies and infrastructure required to support digital innovation. The course covers key web concepts and skills for designing, creating, and maintaining websites.
DGIN 5200 Foundations in Business
The overall aim of this course is to develop a high-level understanding of the dynamics of innovation, the distribution and outcomes of the strategic management of innovation, and the relationships that are important in developing high-impact organizations.
DGIN 5300 Law, Policy, and Ethics in Emerging Technologies
This course offers students an introduction to foundational legal, policy, and ethical issues raised by emerging technologies in a variety of contexts, with special consideration for digital innovation and commerce.
DGIN 5400 Statistics for Health Informatics
This course covers essential statistical methods for medical research, including descriptive analysis techniques and basic principles of statistical inference.
DGIN 5201 Digital Transformation
This core digital innovation course focuses on the design and management of digital innovation projects for both public sector and private sector organizations.
STAT 5620 Data Analysis
This course begins with a thorough description of the multi-disciplinary field of data science, making clear the role of statistics therein. Issues surrounding data ethics and reproducibility will then be discussed.
CSCI 6409 The Process of Data Science
The advent of low-cost storage and processing power coupled with ever-increasing amounts of "born digital" data has created the new field of data science. This course is an overview of the different processes that make up a data science project.
CSCI 6505 Machine Learning
Machine Learning is the area of Artificial Intelligence concerned with the problem of building computer programs that automatically improve with experience.
BUSI/INFO 6513 Business Analytics and Data Visualization
This course provides an introduction to Business Analytics and Data Visualization, covering the processes, methodologies, and practices used to transform large amounts of business and public data into useful information to support business decision-making.
INFO 6681 Geospatial Information Management
This course addresses the effective management of spatial information, covering principles and practices associated with metadata, GIS, licensing, spatial information databases, map libraries, and archives.
STAT 5130 Bayesian Data Analysis
This course covers all the fundamental concepts of Bayesian methods, working from the simplest ideas up through hierarchical models applied to various data.
STAT 5350 Applied Multivariate Analysis
This course deals with the stochastic behavior of several variables in systems where their interdependence is the object of analysis, with greater emphasis placed on practical application than on mathematical refinement.
STAT 5390 Time Series Analysis
Time series analysis in both the time and frequency domain is introduced, with topics including the nature of time series, stationarity, auto and cross-covariance functions, and the Box-Jenkins approach to model identification and fitting.
STAT 5550 Longitudinal Data Analysis
This course is concerned with statistical techniques for analysis of longitudinal data, covering topics such as generalized estimating equations, fixed, random, and mixed effects linear models, and generalized linear models.
CSCI 6405 Data Mining and Data Warehousing
This course gives a basic exposition of the goals and methods of data mining and data warehouses, including concepts, principles, architectures, algorithms, implementations, and applications.
CSCI 6406 Visualization
This course focuses on graphical techniques for data visualization that assist in the extraction of meaning from datasets, involving the design and development of efficient tools for the exploration of large and often complex information domains.
CSCI 6509 Advanced Topics in Natural Language Processing
Natural Language Processing (NLP) is an area of Artificial Intelligence concerned with the problem of automatically analyzing and generating a natural language, such as English, French, or other, in written or spoken form.
CSCI 6515 Machine Learning for Big Data
In this course, we will focus on Big Data and the Pillars of that emerging discipline: machine learning/data mining, elements of high-performance computing, and data visualization.
CSCI 6612 Visual Analytics
This course will introduce the concepts of Visual Analytics (VA), combining data visualization with machine learning and other automated techniques to help people make sense of data.
DGIN 5401 Operationalized Machine Learning in Healthcare
This course provides a broad overview of machine learning and machine learning operations in healthcare contexts, focusing on various graphical, deep learning, time-series, and transfer learning models and unique aspects of their application in healthcare.