Artificial Intelligence and Data Science

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Explore artificial intelligence (AI) and data science through training in predictive, descriptive, and prescriptive analytics, developing skills that can be applied to a range of industries.

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Home / Learn / Programs List / Artificial Intelligence and Data Science

Credential

Ontario College Graduate Certificate

Duration

Two semesters

Start Date(s)

September (Fall)

Locations

Belleville

Open to

International Students

Domestic Students

CIP Code

11.0102

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:

Innovative
Inquisitive
Analytical
Organized
Detail-oriented
Critical reasoning
Statistical thinker

How you'll learn

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.
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.

Courses

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.

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.

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Admission Requirements

Required academic preparation

Ontario College Diploma, Ontario College Advanced Diploma, degree, or equivalent.

International students

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. Learn more about admission requirements for international applicants and how to apply.

This program may be PGWP-eligible. Learn more and explore Loyalist’s PGWP-aligned programs.

Costs

Approximate costs (2024 – 25)

Domestic Tuition: $2,722.08
Full-Time Ancillary Fees:* $1,367
Total: $4,089.08

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 page for a list of the many services, activities and items included within the ancillary fees, and the related policies.

Paying for college

At Loyalist College, we believe that cost should never be a barrier to your success. We’re here to help you navigate the costs of college and connect you with a variety of financial aid programs, resources and donor-supported awards. Explore paying for college.  

Approximate costs (2024 – 25)

International Tuition: $15,000
Full-Time Ancillary Fees:* $1,367
Mandatory Health Insurance: $659
Total: $17,026

Additional costs, such as supplies, travel and parking, may be incurred during workplace visits, etc.

Paying for college

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Further study

Pathways and university transfer

What’s next? Build on the knowledge and skills you learned at Loyalist by continuing your academic journey. Return to Loyalist to complete a second post-graduate program in as little as a year, or receive credit recognition for your Loyalist studies when pursuing a degree at a university. Explore pathway opportunities.

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