When Philip Hestvik signed up for Amii's ML Technician course, he was looking to build on his skills and ready himself to take advantage of new opportunities that artificial intelligence and machine learning know-how can offer. What he wasn't expecting, however, was just how quickly he would begin to see the benefits of the training.

Hestvik was familiar with coding in Python: mostly for personal projects like a script to scrape web data to inform his buying decisions or organize his personal documents. But he was interested in learning more. In his role as a professional engineer with Enbridge, he works with remote sensing data including LiDAR and sonar, which, had him wanting to develop more technical skills. Specifically, he wanted to dive into the rapidly evolving field of machine learning.

"My idea was 'let's take this Amii course.' Let's bring in some machine learning and understand how it works, then see what doors open," Hestvik said.

Job-ready skills in machine learning

Hestvik had tried to upskill through self-directed online courses in the past, but he says it was challenging to connect the material to his daily work. The ML Technician course was different, he says; it allowed him to meet new people, build relationships with them and learn from each other. In the final part of the course, the participants also work together to develop a solution for a capstone project.

He admits it was a bit of a shock getting back into the student mindset. However, Hestvik says he appreciates how ML Tech wasn't just about the technical details but helped students gain a fuller picture of machine learning, the way it can be used and the potential it offers.

"Everybody wants to race into like the coding part. The instructors of the ML Tech and the ML Foundations courses realize how important it is to really set things up. From the basics to when you do your ML final project, it's that full understanding," he says. After taking the course, you look at problems differently because you have a background in ML and you ask yourself, can I apply to this problem?

More and more businesses are recognizing the potential for artificial intelligence and machine learning to transform their operations. This has led to an urgent demand for employees who can understand and effectively work with AI and ML.

The ML Tech course equips people with invaluable skills and knowledge to take advantage of this need for workers with AI experience. The nine-week course builds foundational knowledge about machine learning, followed by the job-ready skills needed to undertake an ML project and apply for positions requiring AI experience. It finishes off with a capstone project, where participants work alongside peers to use real-world data to design an AI-based business solution. At the end of the program, they have the skills to both build a business case for an ML project and undertake it.

Speaking the language of ML

Hestvik went into the ML Tech course with the hope of learning new skills that might open up more career opportunities. But he says he didn't expect how quickly it would happen. He was only about halfway through the program when he saw the benefit his machine learning training could offer.

While still in the course, Hestvik was asked to go on an internal secondment as a product owner, which fit in nicely with his previous experience working with remote sensing data. The new machine learning knowledge he built while training with Amii is also a significant asset, as it allows him to understand the tools his team will be working with.

"I don't need to know how to run the complex machine learning models that data scientists and machine learning engineers have developed. But I know a little bit about machine learning. So I can speak the language they're working on and as a team, we are stronger for it," he says.

"[The ML Tech course] was an impactful, fast-paced learning environment. It added a lot of clarity for me on where I want to go in my career."

“This group’s project stands out as one of the top projects we’ve seen so far in this course. The group put in a lot of work to ensure that the evaluations of their machine learning models aligned with the strategic goals of their organization, NASA, and they also developed a compelling business case with dynamic visualizations, which made the material accessible for both scientists and business experts -- this was largely due to Alejandro’s efforts.“

“After the presentation, we talked about how it went, and we were very happy,” Alejandro shared. “It was a lot of work to get to that point, and it was a relief that everything actually worked. We had a really good business case, and we showed people how impactful it could be. We were very proud of what we did.”

Conclusion

Alejandro now works as a Senior Data Specialist, Data Efficiencies at Alberta Investment Management Corporation (AIMCo). His hobby, which he once pursued on evenings and weekends, has become his career.