The integration of Artificial Intelligence (AI) in the daily roles of a variety of professions is becoming so common that industries previously unaware of its impact are now recognizing its benefits.
However, professionals in software development, computer science, networks, security and other technology fields have long understood that AI would revolutionize the way many work.
Health care sciences are embracing AI to help optimize the development of much-needed treatments to help patients sooner. Manufacturing is looking to chat-bot style programs to help workers pinpoint where factories are using too much energy, creating defects in production, or minimizing the risk of downtime.
Tools for creative roles like design and writing programs are introducing new artificial intelligence features to help minimize manual tasks, to hopefully allow creatives to have more energy for big ideas. Even on our phones, generative AI technology tries to predict how to help us search, type, and write our emails.
The variety of software and technology platforms and websites rolling out AI features is growing at a rate that organizations eager to adopt AI are struggling to keep up with. A 2024 report states that while 50% of surveyed leaders claimed to be allocating 10–30% of their IT budgets specifically towards AI, their IT infrastructure and talent with AI expertise to help make these changes are lacking.
At Mohawk College, we believe there are huge opportunities within these common challenges for students to build on their skills and expand their career potential. The demand for talent versed in AI is high, this is the time for software developers and other computer science students to gain the practical knowledge and experience needed to prepare them to use AI today and help shape its possibilities for tomorrow.
We'll explore what AI is, its current and future applications, its benefits, and how to learn AI. We’ll also introduce our new Graduate Certificate: Applied Artificial Intelligence and provide details on how to apply for an Artificial Intelligence course.
What is AI?
Essentially, Artificial Intelligence is a collection of methodologies and approaches that can help machines simulate tasks that require problem-solving, decision-making, comprehension, creativity and tasks previously believed only human minds could perform.
AI has evolved into various branches, but two of the most prominent today are Traditional AI and Generative AI.
Traditional Artificial Intelligence: The rule-based and predictive approach
Machine Learning
Machine Learning (ML) is the process of having a machine learn from the provided data instead of requiring the machine to follow the parameters of what it has been programmed to follow. Based on the data provided, the machine recognizes patterns or outliers and uses this information to make decisions.
Machine Learning is celebrated for its ability to help automate difficult tasks and make the most logical, informed decision by looking at all the data available. Using this data, the machine creates a model to follow to complete tasks—basically, the machine creates its own program through an algorithm.
Some examples of ML include email filtering, voice-controlled assistant devices like Google Home or Alexa, fraud detection in banking, and genetic research in healthcare.
Deep Learning
Deep Learning (DL) is a large element of the successful ML technology in use today. By using artificial neural networks for complex ML, technology can handle decision-making on new levels, reaching closer to the decision-making abilities of the human mind.
To build artificial neural networks one input layer of data is required but there are typically at least three to hundreds of hidden layers of data beneath that to support the machine’s learning. These layers or nodes, build on each other while analyzing the data to create a final output layer, which determines the decision made by the machine.
Deep Learning fuels AI capabilities like image recognition, chatbots for customer service, financial predictions and tools like Google Translate.
Generative Artificial Intelligence
Generative AI uses Deep Learning to generate new content using a prompt or request. From text, to videos, to images, and even audio, the capabilities of the AI technology known as Generative AI have taken the world by storm.
Examples of Generative AI include:
Large Language Models (LLMs): AI systems like OpenAI’s GPT-4 and Google’s Gemini generate human-like text and assist with creative writing, programming and summarization.
Image and video generation: AI-powered tools like Midjourney, DALL·E, and Stable Diffusion generate realistic images and artwork based on textual prompts.
Code generation: AI models like GitHub Copilot and Amazon CodeWhisperer assist developers by suggesting and completing code.
There are three main stages of Generative AI:
- Training
By building a foundational model from applicable existing content, the training process creates artificial neural networks to analyze the patterns, components, and relationships found in the input data to learn appropriate parameters. - Tuning
Think of tuning a radio to the right frequency for this stage. This is where what you need and what is created must connect. The foundational model needs to be ‘tuned’ by providing prompts to fit the content to your needs or by giving feedback to help the technology understand where it has made an error. - Generation (with stages 1 and 2 often repeated)
Once the content is generated, it is sometimes required to provide better examples or stronger prompts to help the technology understand how to get the content closer to the desired outcome.
Both traditional and generative AI play essential roles in today’s digital world. While traditional AI ensures accuracy, efficiency and automation, generative AI enhances creativity, personalization and innovation. Organizations often combine both approaches to build powerful AI-driven solutions that meet various industry needs.
With the rise in the use of Generation AI tools like ChatGPT, the demand for Generative AI tools that can make manual tasks easier is in high demand. Both branches of AI, Traditional and Generative need people who have AI certifications, AI experience or have completed AI courses to build, maintain and improve this AI technology.
AI-specific roles are on the rise at enterprises around the world and these skills are in demand for software developers especially. But for anyone working in tech, AI is transforming not only the tech industry but also the skills required for those looking to work in the field.
Artificial Intelligence (AI) and the impact on software development
AI is revolutionizing software development in two fundamental ways: AI is becoming a developing assistant and a core feature in software.
1. AI as a development assistant
AI-powered development tools are making software engineering more efficient, secure, and intelligent.
- AI-Powered Code Generation: Tools like GitHub Copilot and OpenAI Codex help developers write code faster and with fewer errors.
- Automated Debugging: AI systems identify vulnerabilities and suggest fixes, improving software security.
- AI-Driven Testing: Tools like Testim and Applitools automate software testing, reducing manual effort.
- Intelligent DevOps: AI enhances continuous integration and deployment (CI/CD) pipelines, streamlining software releases.
2. AI as a core feature in software
AI is not just a tool for developers—it is increasingly embedded into software applications to improve functionality and user experience.
- Personalization: AI-powered recommendation engines in platforms like Netflix and Spotify provide customized content based on user preferences.
- Conversational AI: Virtual assistants like ChatGPT, Google Assistant and Alexa enhance human-computer interactions.
- Automated Decision-Making: AI-powered analytics help businesses make data-driven decisions in finance, healthcare and marketing.
- Predictive Maintenance: AI predicts potential system failures, helping industries avoid costly downtime.
AI is reshaping how software is built and how users interact with technology. Future AI-driven software will:
- Be more autonomous, requiring minimal human intervention for development and maintenance.
- Integrate real-time generative AI capabilities, allowing for personalized and adaptive experiences.
- Improve security through AI-powered threat detection, reducing cybersecurity risks.
As AI continues to evolve, it will become a fundamental part of every aspect of software development, making applications more intelligent, efficient, and adaptable.
"As AI continues to revolutionize industries, professionals who invest in AI skills today are securing their careers for tomorrow. The Applied Artificial Intelligence (AAI) graduate certificate program at Mohawk College equips students with cutting-edge AI knowledge, practical hands-on experience, and industry-relevant skills.
By enrolling in our AAI program, students position themselves at the forefront of AI-driven innovation, ensuring they are prepared for the future job market in this rapidly evolving technological landscape."
— Dr. Amin Azmoodeh, Computer Science Professor & AI Program Coordinator
How to learn AI foundations
With a wide variety of AI-specific positions and more employers looking for hires to have AI experience or training. To learn AI foundations students or recent graduates are going to want to look for Artificial Intelligence courses and programs teaching Applied Artificial Intelligence (AI).
To become proficient in Artificial Intelligence in your career, employers will expect you to have:
- Technical skills
- Theoretical understanding
- Hands-on experience
Applied Artificial Intelligence (AAI) combines the required elements of computer science, mathematics and domain-specific knowledge to build on strong programming skills and help learners effectively use AI in real-world scenarios.
An education in Applied Artificial Intelligence will help students gain experience working with data, the theoretical knowledge of the ethical and regulatory frameworks that govern AI applications, and the technical skills to use their knowledge in future positions.
The best way to learn AI is from experts who can cover a broad range of domains and their applications including:
- Natural Language Processing (NLP) used for chatbots and language translation.
- Machine Vision used for object detection and medical imaging.
- Industrial Control Systems used for automation and predictive maintenance.
Beyond the technical skills and experience, a knowledge of the evolving regulations, ethical considerations, and responsible AI practices are beneficial for a successful career. As technologies evolve, governments and worldwide organizations are continuously implementing and refining new policies to keep Artificial Intelligence systems fair, transparent, and secure.
Understanding AI governance, bias mitigation and the ethical implications of AI-driven decision-making is critical for building AI applications that are not only effective but also socially responsible.
“To learn AI effectively, students need a curriculum that balances hands-on coding experience, real-world datasets, and an understanding of ethical AI practices. The Applied Artificial Intelligence (AAI) Graduate Certificate program at Mohawk College provides an industry-focused education that equips students with the practical skills and knowledge required to build AI-powered solutions across multiple domains.
By gaining experience in AI model development, data processing and AI ethics, students position themselves at the forefront of this transformative field.”
— Dr.Amin Azmoodeh, Computer Science Professor & AI Program Coordinator
Finding the right Artificial Intelligence program
AI technology is rapidly evolving, and the right program needs to do more than just help students learn AI foundations. The best programs will prepare students for the future by staying ahead of technological advancements. By combining theory, hands-on experience, and technical skills, students will have the ability to build test, and refine AI models in real-world scenarios.
While degrees in AI are now available, a graduate certificate program is the best way for those nearing the completion of their studies to gain specialized AI education that builds on their current or previous degree or diploma.
Graduate certificates are designed for those entering the workforce or holding entry-level positions to provide flexible and efficient ways to gain the skills needed to succeed in this rapidly growing field.
Mohawk College: Applied Artificial Intelligence Graduate Certificate
At Mohawk College, our recently introduced graduate certificate program is primed to become one of the leading Artificial Intelligence programs in Canada. The curriculum incorporates the latest methods and tools, and emphasizes practical implementation so students learn AI models and are prepared to apply AI solutions confidently and efficiently.
This program provides students with high-quality learning and hands-on practice, starting with AI foundations before advancing to more complex applications.
Your first semester at a glance
Students will focus on building foundational AI skills, including key concepts in Machine Learning (ML), data processing, and algorithm development. This semester ensures that students gain a solid understanding of AI principles and essential programming techniques.
Your second semester at a glance
Students transition into advanced AI applications, where students learn to apply AI techniques to solve complex problems, gaining deeper insights into real-world implementations.
The program culminates in the AI capstone course, where students integrate their acquired knowledge and skills into a real-world AI project. This final project serves as a demonstration of their expertise, allowing them to showcase their ability to design, develop, and deploy AI-driven solutions.
By the end of the program, graduates will be well-equipped with both theoretical knowledge and practical experience, making them highly competitive in the evolving AI job market.
How to apply
Whether you’re looking for how to apply for an Artificial Intelligence course or searching for AI courses in Canada you’re in the right place. Graduates from the following programs can apply:
- Computer Sciences
- Software Development
- Computer Systems Technology
- Network Engineering and Security Analyst
- Computer Systems Technician
- Software Support
- Computer Systems Technician
- Network Systems
Visit the program page to learn more about this exciting new Artificial Intelligence program.
