Machine learning senior leader helps students launch new careers

Faezeh Heydari Khabbaz

Faezeh Heydari Khabbaz, Instructor, Certificate in Machine Learning

We live in a connected world: wireless devices, artificial intelligence (AI), the Internet of Things (IoT). With that connectivity comes data—a lot of data—and the need for machine learning specialists equipped to not only manage and understand that data but use it ethically to change the world of business.

For this reason, the York University School of Continuing Studies has introduced the only dedicated Certificate in Machine Learning in Canada.

Dr. Faezeh Khabbaz is one of the expert program instructors, and she recently took some time out of her busy schedule as Director of Data Science in Data and Analytics at RBC to answer some questions about the certificate, its value, how she came to be involved with machine learning, and trends and takeaways that you can expect as a student in the program.

What makes machine learning such an exciting career path, and what made you choose it?

Machine learning is the science of detecting patterns in data in order to make accurate predictions for the future. It’s everywhere—from Netflix’s recommendation engine to Google’s self-driving car. The field of machine learning is expanding fast, with different algorithms being applied from apps to emails to marketing campaigns. What is more exciting than being a part of this field?

How did your training & education prepare you to work in the field of machine learning?

My graduate work for both my masters and Ph.D. consisted of a lot of data analysis. In machine learning you need to have a good understanding of a broad set of algorithms and applied math, great problem solving and analytical skills, knowledge of probability and statistics, programming languages, and many other advanced skills which I gained through my graduate work.

How have recent developments changed the field of machine learning, and how will these changes affect the skills or knowledge required for job success?

Machine learning has been around for a long time, but it’s a field that is always changing. When you see these rapid advancements coming out of the field, you realize that to stay relevant you have to keep learning and updating your knowledge. To me, that’s one of the beauties of machine learning.

How has your background and experience in data science and robotics influenced your style of teaching students to approach business problems?

Working in machine learning has led me to believe that the best way to teach students to solve business problems is by working on relevant real-use cases. In my courses, I strive to lessen math and analytics phobias and encourage students to become comfortable with uncertainties in data science use cases. I have learned that the most important lessons for students to learn are not necessarily the most advanced techniques but rather the simple concepts of how to conceptualize, formulate, and model difficult machine learning problems. I introduce problem-solving techniques in the field, including a step-by-step methodology, and then apply these techniques to real-world problems.

Who is your ideal student for this program and why?

Someone with a big appetite for new technology, and a willingness to experiment with new ideas. Someone with the ability to learn independently, a strong sense of curiosity, and confidence.

What skills will students take away from the program that will help them in their future positions?

When they complete the Certificate in Machine Learning, students will have developed a great understanding of a broad set of machine learning algorithms, business problem solving and analytical skills, knowledge of big data tools, and the ability to manage both structured and unstructured data. Students will be able to quickly deliver machine learning solutions by applying effective analytics and sophisticated models to huge volumes of data. Companies are actively recruiting data scientists who are trained in and able to use advanced machine learning algorithms in this way.

What types of jobs can students in the program expect to pursue upon its completion? Why these areas, in particular?

A program like this is valuable for demonstrating competence, allowing you to prove and establish yourself with a strong portfolio of project work. The way that this certificate is designed prepares students for most jobs that are hiring for data scientists or machine learning specialists. Moreover, through the program, the students will get the chance to seek mentoring guidance from instructors and program partners to land a job in the field.

Are there any specific job trends that you see or anticipate in the field of machine learning?

As interest in machine learning grows and the discipline matures, future hiring is likely to be concentrated in areas such as natural language generation, speech recognition, and virtual agents. Expertise gained from the Certificate in Machine Learning through the course and project work prepares students to hit the ground running when it comes time to find a job.

What can a student expect from the machine learning program in terms of commitment required, takeaways, etc.?

In this program, students will learn how to build machine learning systems. The courses are student-centered and offer an accelerated path to completion—the 8-month certificate is available almost entirely online. I expect students to find the workload manageable along with their other commitments.

What advice would you give someone considering this program?

I encourage students to come to the program with a solid understanding of mathematics and statistics, calculus and programming (preferably Python or R). What’s key is that students learn to recognize problems that are best solved with machine learning, and master the skills to formulate, train and deploy them. If you really want to succeed, you need to put in the time. A portfolio of GitHub repositories is becoming your resume for the machine learning field. And remember that your education does not end with this certificate; you should always keep learning. There are great papers, books and blog posts on machine learning that you can leverage in this process.

If you are interested in discovering more about the highly competitive—and highly desirable—field of machine learning, please visit our Certificate in Machine Learning page.