Technology transforms the world in so many ways. Ford’s introduction of the assembly line was essential to the vehicle manufacturing process. The introduction of the internet changed how we communicate, do business, and interact with the world. And in machine learning, we have an emerging technology that transforms how we use computers to complete complex tasks.
Think of machine learning models as “brains” that machines use to actively learn. No longer constrained by rules laid out in their programming, machines have the ability to develop an understanding of new concepts and deliver analysis in ways they never could before. And as a prospective machine learning student, you can become the person who creates the “brains” that modern machines use now and in the future.
But you need a good starting point before you can do any of that. This article covers three of the best machine learning tutorials for beginners who want to get their feet wet while building foundational knowledge that serves them in more specialized courses.
Factors to Consider When Choosing a Machine Learning Tutorial
A machine learning beginner can’t expect to jump straight into a course that delves into neural networking and deep learning and have any idea what they’re doing. They need to learn to crawl before they can walk, making the following factors crucial to consider when choosing a machine learning tutorial for beginners.
- Content quality. You wouldn’t use cheap plastic parts to build an airplane, just like you can’t rely on poor-quality course content to get you started with machine learning. Always look for reviews of a tutorial before engaging, in addition to checking the credentials of the provider to ensure they deliver relevant content that aligns with your career goals.
- Instructor expertise. Sticking with our airplane analogy, imagine being taught how to pilot a plane by somebody who’s never actually flown. It simply wouldn’t work. The same goes for a machine learning tutorial, as you need to see evidence that your instructor does more than parrot information that you can find elsewhere. Look for real-world experience and accreditation from recognized authorities.
- Course structure and pacing. As nice as it would be to have an infinite amount of free time to dedicate to learning, that isn’t a reality for anybody. You have work, life, family, and possibly other study commitments to keep on top of, and your machine learning tutorial has to fit around all of it.
- Practical and real-world examples. Theoretical knowledge can only take you so far. You need to know how to apply what you’ve learned, which is why a good tutorial should have practical elements that test your knowledge. Think of it like driving a car. You can read pages upon pages of material on how to drive properly but you won’t be able to get on the road until you’ve spent time learning behind the wheel.
- Community support. Machine learning is a complex subject and it’s natural to feel a little lost with the materials in many tutorials. A strong community gives you a resource base to lean into, in addition to exposing you to peers (and experienced tech-heads) who can help you along or point you in the right career direction.
Top Three Machine Learning Tutorials for Beginners
Now you know what to look for in a machine learning tutorial for beginners, you’re ready to start searching for a course. But if you want to take a shortcut and jump straight into learning, these three courses are superb starting points.
Tutorial 1 – Intro to Machine Learning (Kaggle)
Offered at no cost, Intro to Machine Learning is a three-hour self-paced course that allows you to learn as and when you feel like learning. All of which is helped by Kaggle’s clever save system. You can use it to save your progress and jump back into your learning whenever you’re ready. The course has seven lessons, the first of which offers an introduction to machine learning as a concept. Whereas the other six dig into more complex topics and come with an exercise for you to complete.
Those little exercises are the tutorial’s biggest plus point. They force you to apply what you’ve learned before you can move on to the next lesson. The course also has a dedicated community (led by tutorial creator Dan Becker) that can help you if you get stuck. You even get a certificate for completing the tutorial, though this certificate isn’t as prestigious as one that comes from an organization like Google or IBM.
On the downside, the course isn’t a complete beginner’s course. You’ll need a solid understanding of Python before you get started. Those new to coding should look for Python courses first or they’ll feel lost when the tutorial starts throwing out terminology and programming libraries that they need to use.
Ideal for students with experience in Python who want to apply the programming language to machine learning models.
Tutorial 2 – What Is Machine Learning? (Udemy)
You can’t build a house without any bricks and you can’t build a machine learning model before you understand the different types of learning that underpin that model. Those different types of learning are what the What is Machine Learning tutorial covers. You’ll get to grips with supervised, unsupervised, and reinforcement learning, which are the three core learning types a machine can use to feed its “brain.”
The course introduces you to real-world problems and helps you to see which type of machine learning is best suited to solving those problems. It’s delivered via online videos, totaling just under two hours of teaching, and includes demonstrations in Python to show you how each type of learning is applied to real-world models. All the resources used for the tutorial are available on a GitHub page (which also gives you access to a strong online community) and the tutorial is delivered by an instructor with over 27 years of experience in the field.
It’s not the perfect course, by any means, as it focuses primarily on learning types without digging much deeper. Those looking for a more in-depth understanding of the algorithms used in machine learning won’t find it here, though they will build foundational knowledge that helps them to better understand those algorithms once they encounter them. As an Udemy course, it’s free to take but requires a subscription to the service if you want a certificate and the ability to communicate directly with the course provider.
Ideal for students who want to learn about the different types of machine learning and how to use Python to apply them.
Tutorial 3 – Machine Learning Tutorial (Geeksforgeeks)
As the most in-depth machine learning tutorial for beginners, the Geeksforgeeks offering covers almost all of the theory you could ever hope to learn. It runs the gamut from a basic introduction to machine learning through to advanced concepts, such as natural language processing and neural networks. And it’s all presented via a single web page that acts like a hub that links you to many other pages, allowing you to tailor your learning experience based on what aligns best with your goals.
The sheer volume of content on offer is the tutorial’s biggest advantage, with dedicated learners able to take themselves from complete machine learning newbies to accomplished experts if they complete everything. There’s also a handy discussion board that puts you in touch with others taking the course. Plus, the “Practice” section of the tutorial includes real-world problems, including a “Problem of the Day” that you can use to test different skills.
However, some students may find the way the material is presented to be a little disorganized and it’s easy to lose track of where you are among the sea of materials. The lack of testing (barring the two or three projects in the “Practice” section) may also rankle with those who want to be able to track their progress easily.
Ideal for self-paced learners who want to be able to pick and choose what they learn and when they learn it.
Additional Resources for Learning Machine Learning
Beyond tutorials, there are tons of additional resources you can use to supplement your learning. These resources are essential for continuing your education because machine learning is an evolving concept that changes constantly.
- Books. Machine learning books are great for digging deeper into the theory you learn via a tutorial, though they come with the downside of offering no practical examples or ways to interact with authors.
- YouTube channels. YouTube videos are ideal for visual learners and they tend to offer a free way to build on what you learn in a tutorial. Examples of great channels to check out include Sentdex and DeepLearningAI, with both channels covering emerging trends in the field alongside lectures and tutorials.
- Blogs and websites. Blogs come with the advantage of the communities that sprout up around them, which you can rely on to build connections and further your knowledge. Of course, there’s the information shared in the blogs, too, though you must check the writer’s credentials before digging too deep into their content.
Master a Machine Learning Tutorial for Beginners Before Moving On
A machine learning tutorial for beginners can give you a solid base in the fundamentals of an extremely complex subject. With that base established, you can build up by taking other courses and tutorials that focus on more specialized aspects of machine learning. Without the base, you’ll find the learning experience much harder. Think of it like building a house – you can’t lay any bricks until you have a foundation in place.
The three tutorials highlighted here give you the base you need (and more besides), but it’s continued study that’s the key to success for machine learning students. Once you’ve completed a tutorial, look for books, blogs, YouTube channels, and other courses that help you keep your knowledge up-to-date and relevant in an ever-evolving subject.
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From the same author
Read the articleOpen Institute of Technology (OPIT) masterclasses bring students face-to-face with real-world business challenges. In OPIT’s July masterclass, OPIT Professor Francesco Derchi and Ph.D. candidate Robert Mario de Stefano explained the principles of regenerative businesses and how regeneration goes hand in hand with growth.
Regenerative Business Models
Professor Derchi began by explaining what exactly is meant by regenerative business models, clearly differentiating them from sustainable or circular models.
Many companies pursue sustainable business models in which they offset their negative impact by investing elsewhere. For example, businesses that are big carbon consumers will support nature regeneration projects. Circular business models are similar but are more focused on their own product chain, aiming to minimize waste by keeping products in use as long as possible through recycling. Both models essentially aim to have a “net-zero” negative impact on the environment.
Regenerative models are different because they actively aim to have a “net-positive” impact on the environment, not just offsetting their own use but actively regenerating the planet.
Massive Transformative Purpose
While regenerative business models are often associated with philanthropic endeavors, Professor Derchi explained that they do not have to be, and that investment in regeneration can be a driver of growth.
He discussed the importance of corporate purpose in the modern business space. Having a strong and clearly stated corporate purpose is considered essential to drive business decision-making, encourage employee buy-in, and promote customer loyalty.
But today, simple corporate missions, such as “make good shoes,” don’t go far enough. People are looking for a Massive Transformational Purpose (MTP) that can take the business to the next level.
Take, for example, Ben & Jerry’s. The business’s initial corporate purpose may have been to make great ice cream and serve it up in a way that people will enjoy. But the business really began to grow when they embraced an MTP. As they announced in their mission statement, “We believe that ice cream can change the world.” Their business activities also have the aim of advancing human rights and dignity, supporting social and economic justice, and protecting and restoring the Earth’s natural systems. While these aims are philanthropic, they have also helped the business grow.
RePlanet
Professor Derchi next talked about RePlanet, a business he recently worked to develop their MTP. Founded in 2015, RePlanet designs and implements customized renewable energy solutions for businesses and projects. The company already operates in the renewable energy field and ranked as the 21st fastest-growing business in Italy in 2023. So while they were already enjoying great success, Derchi worked with them to see if actively embracing a regenerative business model could unlock additional growth.
Working together, RePlanet moved towards an MTP of building a greener future based on today’s choices, ensuring a cleaner world for generations. Meeting this goal started with the energy products that RePlanet sells, such as energy systems that recover heat from dairy farms. But as the business’s MTP, it goes beyond that. RePlanet doesn’t just engage suppliers; it chooses partners that share its specific values. It also influences the projects they choose to work on – they prioritize high-impact social projects, such as recently installing photovoltaic energy systems at a local hospital in Nigeria – and how RePlanet treats its talent, acknowledging that people are the true energy of the company.
Regenerative Business Strategies
Based on work with RePlanet and other businesses, Derchi has identified six archetypal regenerative business strategies for businesses that want to have both a regenerative impact and drive growth:
- Regenerative Leadership – Laying the foundation for regeneration in a broader sense throughout the company
- Nature Regeneration – Strategies to improve the health of the natural world
- Social Regeneration – Regenerating human ecosystems through things such as fair-trade practices
- Responsible Sourcing – Empowering and strengthening suppliers and their communities
- Health & Well-being – Creating products and services that have a positive effect on customers
- Employee Focus – Improve work conditions, lives, and well-being of employees.
Case Studies
Building on the concept of regenerative business models, Roberto Mario de Stefano shared other case studies of businesses that are having a positive impact and enjoying growth thanks to regenerative business models and strategies.
Biorfarm
Biorfarm is a digital platform that supports small-scale agriculture by creating a direct link between small farmers and consumers. Cutting out the middleman in modern supply chains means that farmers earn about 50% more for their produce. They set consumers up as “digital farmers” who actively support and learn about farming activities to promote more conscious food consumption.
Their vision is to create a food economy in which those who produce food and those who consume it are connected. This moves consumers from passive cash cows for large corporations that prioritize profits over the well-being of farmers to actively supporting natural production and a more sustainable system.
Rifo Lab
Rifo Lab is a circular clothing brand with the vision of addressing the problem of overproduction in the clothing industry. Established in Prato, Italy, a traditional textile-producing area, the company produces clothes made from textile waste and biodegradable materials. There are no physical stores, and all orders must be placed online; everything is made to order, reducing excess production.
With an eye on social regeneration, all production takes place within 30 kilometers of their offices, allowing the business to support ethical and local production. They also work with companies that actively integrate migrants into the local community, sharing their local artisan crafts with future generations.
Ogyre
Ogyre is a digital platform that allows you to pay fishermen to fish for waste. When fishermen are out conducting their livelihood, they also collect a significant amount of waste from the ocean, especially plastic waste. Ogyre arranges for fishermen to get paid for collecting that waste, which in turn supports the local fishing communities, and then transforms the waste collected into new sustainable products.
Moving Towards a Regenerative Future
The masterclass concluded with a Q&A session, where it explained that working in regenerative businesses requires the same skills as any other business. But it also requires you to embrace a mindset where value comes from giving and that growth is about working together for a better future, and not just competition.
Read the articleRiccardo Ocleppo’s vision for the Open Institute of Technology (OPIT) started when he realized that his own university-level training had not properly prepared him for the modern workplace. Technological innovation is moving quickly and changing the nature of work, while university curricula evolve slowly, in part due to systems in place designed to preserve the quality of courses.
Ocleppo was determined to create a higher learning institution that filled the gap between the two realities – delivering high-quality education while preparing professionals to work in dynamic environments that keep pace with technology. Thus, OPIT opened enrolments in 2023 with a curriculum that created a unique bridge between the present and the future.
This is the story of one student, Ania Jaca, whose time at OPIT gave her the skills to connect her knowledge of product design to full system deployment.
Meet Ania
Ania is an example of an active professional who was able to identify what was missing in her own skills that would be needed if she wanted to advance her career in the direction she desired.
Ania is a highly skilled professional who was working on product and industrial design at Deloitte. She has an MA in product design, speaks five languages, studied in China, and is an avid boxer. She had the intelligence and the temperament to succeed in her career, but felt that she lacked the skills to advance and move from determining how products look to how systems really work, scale, and evolve.
Ania taught herself skills such as Python, artificial intelligence (AI), and cloud infrastructure, but soon realized that she needed a more structured education to go deeper. Thus, the search for her next steps began, and her introduction to OPIT.
OPIT appealed to Ania because it offered a fully EU-accredited MSc that she could pursue at her own pace, thanks to remote delivery and flexible hours. But more than that, it filled exactly the knowledge gap she was looking to build upon, teaching her technical foundations, but always with a focus on applications in the real world. Part of the appeal was the faculty, which includes professionals who are leaders in their field and who deal with current professional challenges on a daily basis, which they can bring into the classroom.
Ania enrolled in OPIT’s MSc in Applied Data Science & AI.
MSc in Applied Data Science and AI
This is OPIT’s first master’s program, which also launched in 2023, and is now one of four on offer. The course is designed for graduates like Ania who want a career at the intersection of management and technology. It is attractive to professionals who are already working in this area but lack the technical training to step into certain roles. OPIT requires no computer science prerequisites, so it accepted Ania with her MA in product design.
It is an intensive program that starts with foundational application courses in business, data science, machine learning, artificial intelligence, and problem-solving. The program then moves towards applying data science and AI methodologies and tools to real-life business problems.
The course combines theoretical study with a capstone project that lets students apply what they learn in the real world, either at their existing company or through internship programs. Many of the projects developed by students go on to become fundamental to the businesses they work with.
Ania’s Path Forward
Ania is working on her capstone project with Neperia Group, an Italian-based IT systems development company that works mostly with financial, insurance, and industrial companies. They specialize in developing analysis tools for existing software to enhance insight, streamline management, minimize the impact of corrective and evolutionary interventions, and boost performance.
Ania is specifically working on tools for assessing vulnerabilities in codebases as an advanced cybersecurity tool.
Ania credits her studies at OPIT for helping her build solid foundations in data science, machine learning, and cloud workflows, giving her a thorough understanding of digital products from end to end. She feels this has prepared her for roles at the intersection between infrastructure, security, and deployment, which is exactly where she wants to be. OPIT is excited to see where Ania’s career takes her in the coming years.
Preparing for the Future of Work
Overall, studying at OPIT has helped Ania and others like her prepare for the future of work. According to the Visual Capitalist, the fastest-growing jobs between 2025 and 2030 will be in big data (up by 110%), Fintech engineers (up by 95%), AI and machine learning specialists (up by 85%), software application developers (up by 60%), and security management specialists (up by 55%).
However, while these industries are growing, entry-level opportunities are declining in areas such as software development and IT. This is because AI now performs many of the tasks associated with those roles. Instead, companies are looking for experienced professionals to take on roles that involve more strategic oversight and innovative problem-solving. But how do recent graduates leapfrog past experienced professionals when there is a lack of entry-level positions to make the transition?
This is another challenge that OPIT addresses in its course design. Students don’t just learn the theory, OPIT actively encourages them to focus on applications, allowing them to build experience while studying. The capstone project consolidates this, enabling students to demonstrate to future employers their expertise at deploying technology to solve problems.
OPIT also has a dynamic Career Services department that specifically works with students to prepare them for the types of roles they want. This focus on not only learning but building a career is one of the elements that makes OPIT stand out in preparing graduates for the workplace.
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Related posts
Open Institute of Technology (OPIT) masterclasses bring students face-to-face with real-world business challenges. In OPIT’s July masterclass, OPIT Professor Francesco Derchi and Ph.D. candidate Robert Mario de Stefano explained the principles of regenerative businesses and how regeneration goes hand in hand with growth.
Regenerative Business Models
Professor Derchi began by explaining what exactly is meant by regenerative business models, clearly differentiating them from sustainable or circular models.
Many companies pursue sustainable business models in which they offset their negative impact by investing elsewhere. For example, businesses that are big carbon consumers will support nature regeneration projects. Circular business models are similar but are more focused on their own product chain, aiming to minimize waste by keeping products in use as long as possible through recycling. Both models essentially aim to have a “net-zero” negative impact on the environment.
Regenerative models are different because they actively aim to have a “net-positive” impact on the environment, not just offsetting their own use but actively regenerating the planet.
Massive Transformative Purpose
While regenerative business models are often associated with philanthropic endeavors, Professor Derchi explained that they do not have to be, and that investment in regeneration can be a driver of growth.
He discussed the importance of corporate purpose in the modern business space. Having a strong and clearly stated corporate purpose is considered essential to drive business decision-making, encourage employee buy-in, and promote customer loyalty.
But today, simple corporate missions, such as “make good shoes,” don’t go far enough. People are looking for a Massive Transformational Purpose (MTP) that can take the business to the next level.
Take, for example, Ben & Jerry’s. The business’s initial corporate purpose may have been to make great ice cream and serve it up in a way that people will enjoy. But the business really began to grow when they embraced an MTP. As they announced in their mission statement, “We believe that ice cream can change the world.” Their business activities also have the aim of advancing human rights and dignity, supporting social and economic justice, and protecting and restoring the Earth’s natural systems. While these aims are philanthropic, they have also helped the business grow.
RePlanet
Professor Derchi next talked about RePlanet, a business he recently worked to develop their MTP. Founded in 2015, RePlanet designs and implements customized renewable energy solutions for businesses and projects. The company already operates in the renewable energy field and ranked as the 21st fastest-growing business in Italy in 2023. So while they were already enjoying great success, Derchi worked with them to see if actively embracing a regenerative business model could unlock additional growth.
Working together, RePlanet moved towards an MTP of building a greener future based on today’s choices, ensuring a cleaner world for generations. Meeting this goal started with the energy products that RePlanet sells, such as energy systems that recover heat from dairy farms. But as the business’s MTP, it goes beyond that. RePlanet doesn’t just engage suppliers; it chooses partners that share its specific values. It also influences the projects they choose to work on – they prioritize high-impact social projects, such as recently installing photovoltaic energy systems at a local hospital in Nigeria – and how RePlanet treats its talent, acknowledging that people are the true energy of the company.
Regenerative Business Strategies
Based on work with RePlanet and other businesses, Derchi has identified six archetypal regenerative business strategies for businesses that want to have both a regenerative impact and drive growth:
- Regenerative Leadership – Laying the foundation for regeneration in a broader sense throughout the company
- Nature Regeneration – Strategies to improve the health of the natural world
- Social Regeneration – Regenerating human ecosystems through things such as fair-trade practices
- Responsible Sourcing – Empowering and strengthening suppliers and their communities
- Health & Well-being – Creating products and services that have a positive effect on customers
- Employee Focus – Improve work conditions, lives, and well-being of employees.
Case Studies
Building on the concept of regenerative business models, Roberto Mario de Stefano shared other case studies of businesses that are having a positive impact and enjoying growth thanks to regenerative business models and strategies.
Biorfarm
Biorfarm is a digital platform that supports small-scale agriculture by creating a direct link between small farmers and consumers. Cutting out the middleman in modern supply chains means that farmers earn about 50% more for their produce. They set consumers up as “digital farmers” who actively support and learn about farming activities to promote more conscious food consumption.
Their vision is to create a food economy in which those who produce food and those who consume it are connected. This moves consumers from passive cash cows for large corporations that prioritize profits over the well-being of farmers to actively supporting natural production and a more sustainable system.
Rifo Lab
Rifo Lab is a circular clothing brand with the vision of addressing the problem of overproduction in the clothing industry. Established in Prato, Italy, a traditional textile-producing area, the company produces clothes made from textile waste and biodegradable materials. There are no physical stores, and all orders must be placed online; everything is made to order, reducing excess production.
With an eye on social regeneration, all production takes place within 30 kilometers of their offices, allowing the business to support ethical and local production. They also work with companies that actively integrate migrants into the local community, sharing their local artisan crafts with future generations.
Ogyre
Ogyre is a digital platform that allows you to pay fishermen to fish for waste. When fishermen are out conducting their livelihood, they also collect a significant amount of waste from the ocean, especially plastic waste. Ogyre arranges for fishermen to get paid for collecting that waste, which in turn supports the local fishing communities, and then transforms the waste collected into new sustainable products.
Moving Towards a Regenerative Future
The masterclass concluded with a Q&A session, where it explained that working in regenerative businesses requires the same skills as any other business. But it also requires you to embrace a mindset where value comes from giving and that growth is about working together for a better future, and not just competition.
Riccardo Ocleppo’s vision for the Open Institute of Technology (OPIT) started when he realized that his own university-level training had not properly prepared him for the modern workplace. Technological innovation is moving quickly and changing the nature of work, while university curricula evolve slowly, in part due to systems in place designed to preserve the quality of courses.
Ocleppo was determined to create a higher learning institution that filled the gap between the two realities – delivering high-quality education while preparing professionals to work in dynamic environments that keep pace with technology. Thus, OPIT opened enrolments in 2023 with a curriculum that created a unique bridge between the present and the future.
This is the story of one student, Ania Jaca, whose time at OPIT gave her the skills to connect her knowledge of product design to full system deployment.
Meet Ania
Ania is an example of an active professional who was able to identify what was missing in her own skills that would be needed if she wanted to advance her career in the direction she desired.
Ania is a highly skilled professional who was working on product and industrial design at Deloitte. She has an MA in product design, speaks five languages, studied in China, and is an avid boxer. She had the intelligence and the temperament to succeed in her career, but felt that she lacked the skills to advance and move from determining how products look to how systems really work, scale, and evolve.
Ania taught herself skills such as Python, artificial intelligence (AI), and cloud infrastructure, but soon realized that she needed a more structured education to go deeper. Thus, the search for her next steps began, and her introduction to OPIT.
OPIT appealed to Ania because it offered a fully EU-accredited MSc that she could pursue at her own pace, thanks to remote delivery and flexible hours. But more than that, it filled exactly the knowledge gap she was looking to build upon, teaching her technical foundations, but always with a focus on applications in the real world. Part of the appeal was the faculty, which includes professionals who are leaders in their field and who deal with current professional challenges on a daily basis, which they can bring into the classroom.
Ania enrolled in OPIT’s MSc in Applied Data Science & AI.
MSc in Applied Data Science and AI
This is OPIT’s first master’s program, which also launched in 2023, and is now one of four on offer. The course is designed for graduates like Ania who want a career at the intersection of management and technology. It is attractive to professionals who are already working in this area but lack the technical training to step into certain roles. OPIT requires no computer science prerequisites, so it accepted Ania with her MA in product design.
It is an intensive program that starts with foundational application courses in business, data science, machine learning, artificial intelligence, and problem-solving. The program then moves towards applying data science and AI methodologies and tools to real-life business problems.
The course combines theoretical study with a capstone project that lets students apply what they learn in the real world, either at their existing company or through internship programs. Many of the projects developed by students go on to become fundamental to the businesses they work with.
Ania’s Path Forward
Ania is working on her capstone project with Neperia Group, an Italian-based IT systems development company that works mostly with financial, insurance, and industrial companies. They specialize in developing analysis tools for existing software to enhance insight, streamline management, minimize the impact of corrective and evolutionary interventions, and boost performance.
Ania is specifically working on tools for assessing vulnerabilities in codebases as an advanced cybersecurity tool.
Ania credits her studies at OPIT for helping her build solid foundations in data science, machine learning, and cloud workflows, giving her a thorough understanding of digital products from end to end. She feels this has prepared her for roles at the intersection between infrastructure, security, and deployment, which is exactly where she wants to be. OPIT is excited to see where Ania’s career takes her in the coming years.
Preparing for the Future of Work
Overall, studying at OPIT has helped Ania and others like her prepare for the future of work. According to the Visual Capitalist, the fastest-growing jobs between 2025 and 2030 will be in big data (up by 110%), Fintech engineers (up by 95%), AI and machine learning specialists (up by 85%), software application developers (up by 60%), and security management specialists (up by 55%).
However, while these industries are growing, entry-level opportunities are declining in areas such as software development and IT. This is because AI now performs many of the tasks associated with those roles. Instead, companies are looking for experienced professionals to take on roles that involve more strategic oversight and innovative problem-solving. But how do recent graduates leapfrog past experienced professionals when there is a lack of entry-level positions to make the transition?
This is another challenge that OPIT addresses in its course design. Students don’t just learn the theory, OPIT actively encourages them to focus on applications, allowing them to build experience while studying. The capstone project consolidates this, enabling students to demonstrate to future employers their expertise at deploying technology to solve problems.
OPIT also has a dynamic Career Services department that specifically works with students to prepare them for the types of roles they want. This focus on not only learning but building a career is one of the elements that makes OPIT stand out in preparing graduates for the workplace.
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