Artificial Intelligence and Data Science
Available as a one-year program
One-year Ontario College Graduate Certificate
- Start Date
Find Your Career
AI and data science professionals find careers working in a range of sectors, including consulting firms, financial services, government and authority, international organizations/non-profits, technology, and research. Graduates could find themselves working as:
- information systems analysts and consultants
- database analysts
- data administrators
- software engineers and designers
Individuals may be employed to work independently or as a member of a team to analyze, design, enhance, and maintain AI systems in various positions in a variety of sectors including, but not limited to:
- Consulting Firms
- Financial Services
- Insurance, real estate, and leasing services
- Government and Authorities
- International Organizations/Non-Profits
- Technology, telecommunications, information, and culture services
- Research and Academic Institutions
- Computer systems design and related services
Is it for you?
Successful students in this program have an interest in cyber security, machine learning, new technological or data science and have the below characteristics:
- Critical reasoning
- Statistical thinker
With this hands-on program, gain the knowledge and skills needed to support an organizations’ AI and Data needs:
- Develop the skills required to collect, manipulate and mine data sets
- Analyze, design, and implement AI systems through the application of systematic approaches and methodologies to meet organizational needs
- Recommend different systems architectures and data storage technologies to support data analytics
- Design and apply data models that meet the needs of a specific operational/business process
- Develop software applications to manipulate data sets, correlate information and produce reports
- Design and present data visualizations to communicate information, analysis, reports, and make recommendations in a variety of formats for various audiences and stakeholders as required to meet operational/business or project objectives
- Apply data analytics, business intelligence tools and research to support evidence-based decision making
- Identify and assess data analytics business strategies and workflows to respond to new opportunities or provide project solutions
- Implement data solutions in compliance with corporate policies, ethical standards, and industry regulations
- Develop AI models and agents that use enterprise data to identify patterns, provide insights, recommend actions or perform tasks autonomously on behalf of stakeholders
Graduates from this program could also earn credits if they chose to further their studies in a related field.
- First Year - Semester One
- AIGS1005 AI Principles and Best Practices in Canada
In this course students will learn about the principles of artificial intelligence and data science and how to apply best practices to their
work within a Canadian industry context.
- AIGS1006 Deep Learning
- This course represents concepts of deep learning such as basics of neural networks, deep neural networks and recurrent neural networks (RNN). Topics covered include the fundamentals of artificial neural networks and how to implement them in Python programming language.
- AIGS1004 Deterministic Models and Optimization
The main objective in this course is to provide students with a thorough grounding in optimization models, theory and algorithms. The course scope is broad, covering the most important representative models and algorithms. Material will be closely linked to modern statistical
methods such as network analysis, Quintilian regression and high dimensional statistics.
- AIGS1003 Machine Learning
- This course introduces students to some of the basic techniques of machine learning required for data science. It provides a solid training in computational algorithms for supervised problems (classification and regression), such as decision trees and forests, support vector machines or nearest neighbours. There is a hands-on, lab section that focuses on the use of scientific scripting languages and special attention is devoted to Python language.
- AIGS1002 Mathematics for Data Science
This course covers fundamental mathematical concepts relevant to data and computer science and provides a basis for further study in data science, statistics and cyber security. Topics covered are probability: sets, counting, probability axioms, Bayes theorem; optimization and calculus: differentiation, integration, functions of several variables, series approximations, gradient descent;
linear algebra: vectors and matrices, matrix algebra, vector spaces; and, discrete mathematics: induction, difference equations. This course helps make connections between each of these fundamental mathematical concepts and modern data science applications. It also leverages Python programming for data wrangling, algorithms and visualization.
- AIGS1000 Programming Languages for AI- Python R
In this course, you’ll learn the fundamentals of Python and R programming languages and explain why they’re the best options for data science projects. Data structures, data manipulation, data
exploration, loops and conditions, and data visualizations will be explored.
- AIGS1001 Statistical Modelling and Inference
- In this course students will be exposed to the concepts of probability and statistics. Probability and statistics form the basis of data science. The probability theory is important for predicting. Estimates and predications form an important part of data science. This course explains how we can make estimates for further analysis using statistics and includes the basis of statistics such as central tendency theorem and types of distribution.
- First Year - Semester Two
- AIGS1014 Capstone Project
- This capstone project will enable you to work on real-world problems using public data. You will apply exploratory data analysis skills to build an accurate prediction model.
- AIGS1010 Computer Vision
- This course presents concepts and fundamentals of computer vision. Image processing and computer vision techniques such as objective detection, object tracking and action recognition will be covered, as well as image segmentation and synthesis.
- AIGS1009 Data Storytelling Techniques
- This course will cover the fundamentals of effective data-driven storytelling. Students will learn how to detect and articulate the stories behind data sets and communicate data findings in visual, oral and written contexts for various audiences and stakeholders. During this course, students will become familiar with associated tools.
- AIGS1007 Data Visualization
- This course focuses on data visualization and explains visualization tools. Topics covered include various data sources, metadata, data preparation, joints and data blending. Basic functions such as sorting and filtering will be included in this course and techniques such as drill down and hierarchies, reference lines and trend lines will be explored.
- AIGS1008 Data Warehousing and Business Intelligence
In this course, you’ll get an overview of modern solutions to storing and analyzing big data, as well as hands on practice working with databases, building systems to collect data from the internet
and crating live web dashboards. You’ll be encouraged to think creatively and use knowledge from other courses from the first semester to come up with an informative display of data that you can
create with the dashboard tools taught in class.
- AIGS1011 Natural Language Processing
This course presents the concept of natural language processing (NLP), the concepts of text mining and its applications, the basics of NLP such as POS, entity recognition, regular expression and how
to implement them. Sentiment analysis, topical modelling and clustering in text courses will be also be covered.
- AIGS1012 Professional Portfolio
- A carefully prepared and professionally presented portfolio provides you with a valuable advantage in the highly competitive process of securing employment. In a broader sense, a portfolio gives you a measure of control over your future, which is particularly important in times of rapid change and economic upheaval. Practical tips, tools, practices, and approaches are addressed to create your unique portfolio of talents, professional skills, experiences and background.
*Courses subject to change.
Within Loyalist College, graduates of this program would be well suited to continue their studies in the FinTech, Cyber Security, or other computer technology related graduate certificate programs.
How much will it cost?
Approximate costs (2022 – 23)
- Domestic Tuition: $2,722.08
- Full-Time Ancillary Fees:* $1,462
- Total: $4,184.08
Additional costs, such as supplies, travel and parking, may be incurred during workplace visits, etc.
*Fees related to programs that are less than or greater than two semesters will be adjusted accordingly. Fees are subject to change. Please visit the Tuition and Fees web page for a list of the many services, activities and items included within the ancillary fees, and the related policies.
Bursaries and financial assistance
Loyalist College has a number of scholarships, bursaries and academic awards available to students. Our Financial Aid Office can help you explore your options, or assist you with a student loan.
Required academic preparation
Ontario College Diploma, Ontario College Advanced Diploma, degree, or equivalent.
All teaching within Loyalist College is conducted in English. In order to be successful in a program, skills such as communication, listening, comprehension, and reading and writing must be at a level sufficient to meet the demands of post-secondary studies. All applicants to Loyalist whose first language is not English, or whose previous education was in another language, will be expected to provide an English proficiency assessment for admissions approval.
Prior learning assessment and recognition
Applicants with work experiences or other types of non-credentialed learning may be eligible for credits at Loyalist. Graded credits (as opposed to exemptions) are granted. Click here for more information about our assessment and credit challenge process.
How to Apply
For details about how to apply for this program, click here (for both international and domestic applicants).
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