By Mike Scott
Summary
Every time you’ve chatted with a bot on a website, you’ve seen the basis of artificial intelligence (AI) and machine learning (ML) in action. Your experiences with augmented reality, any prompts you’ve ever delivered to ChatGPT, and a host of other technologies that businesses are already leveraging show us how crucial these two fields are, both today and in the future.
AI and ML are taking over the world. And with the right AI & ML courses, you put yourself in the ideal position to forge a career in an industry that’s set for a continuous annual growth rate of 36.2% between 2023 and 2030.
AI ML courses come in all shapes and sizes, with some delivering the basics you need to build a foundation in the subjects and others moving on from those foundational concepts and into specializations. These five things are your biggest considerations when choosing a course.
What does the course teach? That’s not just an important question in terms of figuring out if the course helps you develop the skills you need, but it’s a crucial one for your future career prospects. The curriculum informs every step you take on your learning journey. If the content isn’t up to scratch (or takes you in a different direction than the one you intend to go in) it’s not the course for you.
Combine work and family with your personal life and existing educational commitments and you have the recipe for a quagmire of time-consuming tasks that may not fit with a long-term course. The best AI and ML courses online offer flexibility, allowing you to fit your studies around other commitments and opening the door to self-paced learning.
Imagine you walk into a classroom and your instructor introduces themself. They tell you they have a couple of qualifications in the fields of AI and ML, but they haven’t worked in either industry and can’t expose you to professionals who have. Is that any use to you in your career? A good instructor combines technical expertise (which they’ll need a lot of) with industry experience they can draw on to lead you down the right career path.
As any online marketer will tell you, user-generated content in the form of reviews, social media posts, and simple ratings tells you a ton about what a product delivers. That’s as true for AI and machine learning courses as it is for anything else. Check out what other people have to say about the course, paying special attention to former students and what’s happened to them in the wake of earning their certification.
Money is always a challenge when it comes to education. Some universities charge tens of thousands of euros for their courses, which is fine if you can commit time and money to a full-time educational experience. It’s not so fine if you’re working on a budget. Your course’s cost plays a huge role in determining whether you take it. Just remember one thing – people tend to get what they pay for (for better or worse).
Machine learning and artificial intelligence courses run the gamut from fast, industry-led courses designed to get you into a job to deeper degrees designed to equip you with everything you need to advance in your career. The following four are some of the best AI and ML courses online.
Designed for those at the postgraduate level, this Master’s degree requires you to have a background in computer science (or a relevant alternative). It’s a 100% online course that delivers an accredited degree under the European Qualification Framework (EQF), with the course also counting toward the college credits you may need to apply for future courses. Tutors are available for direct learning 24/7 and you learn via both recorded and live content delivered over the web.
OPIT’s Master in Applied Data Science & AI comes in two flavors – the regular 18-month variety and a fast-tracked 12-month course. Enrollment is annual, with intake occurring every October, and the price varies depending on when you apply. Early birds get an extensive discount, paying €4,950 compared to the regular price of €6,500. You’ll need a relevant Bachelor’s degree in a subject like computer science to apply.
If OPIT’s Master’s degree is for people who are already halfway through the metaphorical marathon of machine learning and AI, IBM’s beginner’s course is for those at the starting line. It’s a seven-hour course that teaches the basics of AI and ML, in addition to helping you get to grips with the development cycle for a machine learning model. As a primer for the concepts, it’s one of the best AI ML online courses available.
“Free” is always a nice price tag to see on anything, and that’s what you get with this course, at least when trialing the course. Enrolment is semi-regular, with batches of students accepted every few months, and you get to reset deadlines based on when you can complete its modules. IBM says the course contains seven hours of content. Your experience may vary depending on how quickly (or otherwise) you adapt to the content.
Career Karma ranks this as one of the best AI ML courses online, and it’s hard to argue given that this is a near-year-long course offered with backing from industry professionals at IBM. It’s more bootcamp than formal course, though, so expect to be put through your paces with intensive hackathons and sprints that cover a huge number of AI tools. Combine that with real-world projects (using datasets from companies like Twitter and Uber) and you have a fast-paced and valuable course.
Enrollment is set for May of each year, with the course lasting for 11 months thereafter. You’ll need to hit some criteria to apply. The course asks for a minimum of a Bachelor’s degree where you’ve obtained at least 50% on your modules, as well as a couple of years of work experience. That work experience requirement may be an issue for people who haven’t started their careers. Still, it’s a cost-effective program, with the course costing £2,990 (approx. €3,400).
If time is of the essence and you just want a crash course in what machine learning is and how it applies to your business, Google provides the answer with this option. At just 15 hours, it’s a course you can complete over an intensive weekend of study. It’ll introduce you to some real-world case studies, with lectures coming directly from industry heads at Google.
Google presumes no prior knowledge of machine learning in this course, though it recommends that you’re comfortable with programming in Python and understand complex statistical concepts. Knowledge of the NumPy library is especially helpful. Assuming you build up a knowledge base (Google offers other courses to cover these foundations), you can enroll at any time and get a free course that you can fit around your schedule.
Great AI ML courses can teach you the fundamentals and offer direct experience, ideally coming from professionals in the industry. But it’s what you do outside of your formal and certified studies that can make the biggest difference to your career prospects. These additional resources both supplement what you learn from the above courses and allow you to continue developing your skills once you have your shiny new certificate:
Consider these facts if you need any more convincing that AI and machine learning courses are right for you. The average machine learning engineer earns between €66,585 and €118,169 per year, with jobs in AI easily climbing into the six-figure range as well. Your career prospects get a boost when you study AI and ML. But remember – a certification alone is not enough.
These are fast-evolving fields, and only those who dedicate themselves to continued learning (and the adaptation that comes with market changes) excel. Start your journey with one of the four courses in this article and then continue down the educational path.
Source:
By Stephanie Mullins
We spoke to education experts from around the world to find out. From Germany’s Frankfurt School of Finance & Management and Nottingham Business School in the UK to India’s IIM Indore and Italy’s POLIMI Graduate School of Management, here’s what 21 experts actually said…
By prioritising these areas, students can better equip themselves to meet the challenges and seize the opportunities of their academic and professional futures.
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