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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Credential

Ontario College Graduate Certificate

Duration

One year or less

Start Date(s)

September (Fall)

Locations

Belleville

Open to

International Students

Note: This is a non-funded program and is therefore not OSAP eligible.

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. Develop essential skills in the following:

Statistical modelling and inference
Machine learning
Data visualization
Data warehousing
Business intelligence
Computer vision
Python

How you'll learn

Through training in predictive, descriptive and prescriptive analytics, gain the knowledge needed to design and build decision-making systems based on AI and data science. Get hands-on skills in the following:

Learn how to collect, manipulate and mine data sets to meet organizational need.
Acquire skills for designing and applying process-specific data models, as well as for developing software applications to manipulate data sets, correlate information and produce reports.
Gain experience identifying and assessing data analytics, business strategies and workflows to respond to new opportunities or provide project solutions.
Develop skills in data analytics, business intelligence tools and research to support evidence-based decision-making.
Practise developing AI models and agents that use enterprise data to identify patterns, provide insights, recommend actions or perform tasks autonomously, on behalf of stakeholders.
A co-op work term or experiential learning opportunity of an academic program of study provides students with relevant and applied industry

Co-op work terms are valuable work-integrated learning experiences that allow students to demonstrate their skills in real-world environments with industry support. The market for co-op employment is competitive, and students are expected to participate actively in their job searches. Students, with support, will be expected to identify and secure a co-op work term experience. Co-op work terms are subject to student eligibility, availability, and program review. If unable to secure or participate in a co-op work term, students will complete an alternative experiential learning opportunity.

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.

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 (PLAR)

Do you have work experience or other types of non-credentialed learning? Through Loyalist’s PLAR program, applicants and current students may be eligible to receive academic credit for relevant educational, work and life experiences.

How to Apply

Both international and domestic applicants can learn about how to apply for this program here.

Costs

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.

*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.

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Further study

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.

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