Growth is inevitable in the AI sector. According to Statista, the already-booming industry looks set to go from a value of $100 billion in 2021 to $2 trillion by 2030, increasing by a multiple of 20 to become one of the world’s biggest industries. Naturally, the need for skilled AI professionals will grow alongside that enormous scaling.

That’s where you come in.

With the right applied AI course, you can develop both the knowledge of the foundational theory that sits behind AI and learn how to apply that theory in a real-world setting. Here are four of the best applied AI courses to get you started.

Factors to Consider When Choosing an Applied AI Course

Every search for a new course starts with figuring out the strengths and weaknesses of each one you consider. These factors help you do that, ensuring you don’t spend your hard-earned money on a course that fails to equip you with skills that make you desirable to employers.

Course Content and Curriculum

AI is such an expansive field that every applied AI course has the potential to cover different topics and subjects. Think about what you want to learn (and your prospective career path), then align your course selection with that intended path.

Course Duration

Applied AI courses can vary tremendously in length, from several years for degree-level courses to a few months for online courses. Ask yourself how long you wish to spend studying. Also, consider the flexibility of the course, such as whether you’ll be able to fit your studies around your existing work and family commitments.

Instructor Expertise

AI is a burgeoning industry, meaning expertise levels vary from course to course. For applied AI courses, in particular, you want professors who combine in-depth knowledge of the theory with real-world experience. What have they done in the industry? If the answer is “nothing,” they may not be able to guide you down the path to an AI-centric career.

Course Fees and Financial Aid

Course fees vary massively depending on the type of course you take. For example, those in the U.K. can easily spend between £15,000 and £25,000 on university-level courses, with Aston University’s tuition fees of £23,200 being somewhat typical. Online and self-learning courses cost considerably less, so you need to figure out how much you’re willing to spend (and if you can get any help with your fees) before moving forward.

Job Placement and Career Support

Though you need one eye pointed toward the present when choosing between applied AI courses, the other needs to be firmly pointed toward the future. What prospects will you have when you complete the course? In other words, does the course provide you with a direct path into the industry, along with support, or are you left to fend for yourself once you have your qualification?

Top Choices for Mastering Artificial Intelligence

Choices abound when you jump online to find applied AI courses. The following selection offers a nice mix, from online certifications offered by industry professionals to a couple of courses from some of the world’s most prestigious universities.

Course 1 – IBM Applied AI Professional Certification

If you’re fresh to the world of AI (though ideally not new to computer science), IBM’s industry-specific applied AI courses offer both foundational knowledge and a respected qualification. They’re flexible, too, with this course lasting for six months but only requiring three hours of work per work. Those in full-time work (or education) can fit the course around their lifestyle, while those who have time to burn can complete the entire course much quicker, earning degree credits along the way.

Key Features and Benefits

  • Certification from one of the most respected companies in the AI space
  • Direct exposure to use cases in the deep learning, machine learning, and neural network spheres
  • Learn how to build AI-powered solutions (like chatbots) using Python and IBM’s Watson AI
  • Over three-quarters (77%) of students report career improvement

Pricing and Enrollment

IBM’s course is available via Coursera and offers a seven-day trial you can use to get to grips with its structure and examine its modules. It’s fully online, which improves flexibility at the cost of not having direct access to a professor, and you’ll receive an IBM badge upon completion. You’ll pay a monthly fee of $35 (approx. €31) and can enroll at almost any time.

Course 2 – Computer Science for Artificial Intelligence (Harvard University)

Harvard University may be seen as the gold standard in the United States, but what many don’t know is that it offers a comprehensive suite of online courses that almost anybody can take. Its Computer Science for Artificial Intelligence course is a perfect example. Comprising of two courses – an introduction to computer science followed by an introduction to applying computer science principles to AI using Python – it lasts for five months. You get access to professors and can learn at your own pace, with the course recommending between seven and 22 hours of study per week.

Key Features and Benefits

  • Two modules give you a crash course in applied AI and the computer science theory that underpins it
  • Director access to Harvard professors Doug Lloyd, Brian Yu, and David J. Malan
  • Complete flexibility in how and when you learn
  • Get to grips with Python and build experience with machine learning libraries

Payment and Enrollment

As an online course, Computer Science for Artificial Intelligence is available for enrollment whenever you’re ready, with the five months starting once you’re enrolled. It costs £277 (approx. €312) and you’ll need to create an account with the EDX website (which hosts the course) to get started.

Course 3 – Artificial Intelligence Graduate Certificate (Stanford University)

Ranked as the third-best university in the United States for general computer science and AI teaching, Stanford University has opened up some of its best courses to online learners. Entirely online (and instructor-led for those who want more guidance) this is one of those applied AI courses that is equivalent to a full graduate degree. You’ll complete at least one required course – with a choice between machine learning and the principles of AI – and select up to three electives. It’s the electives that make this course stand out, as there are 18 to choose from, with the right combination giving you a chance to specialize for specific career paths.

Key Benefits and Features

  • Direct tuition from prominent Stanford faculty members, including Andrew Ng and Chelsea Finn
  • Some level of autonomy in how you study thanks to the online-centric nature of the course
  • Specialize in specific areas of AI thanks to a wide range of electives
  • You get a degree from one of the world’s foremost colleges in the AI field

Payment and Enrollment

Let’s get the bad news out of the way immediately – this isn’t a cheap course. As a full-on graduate degree, it costs between $18,200 and $22,400 to take (approx. €16,235 and €19,980), though financial aid may be available for some students. You can’t just hop onto the course, either, as a college-level understanding of calculus, linear algebra, Probability Theory, and several programming languages is required. Stanford itself calls this one of its most difficult courses and recommends that you take several foundation courses (ideally at degree level) before enrolling.

Course 4 – Master in Applied Data Science & AI (OPIT)

As a full postgraduate course that takes between 12 and 18 months to complete, OPIT’s Master in Applied Data Science & AI is an interesting case for one simple reason – there are no computer science prerequisites. The course is open to everybody and it teaches both advanced applied AI concepts and the foundational knowledge needed to understand them. You’ll complete a pair of terms containing courses, with your final term dedicated to a project or thesis that puts what you’ve learned into practice.

Key Benefits and Features

  • The course is supplied by an institution with accreditation from the European Qualification Framework
  • It’s a fully remote course that gives you control over how and when you learn
  • Discounts and payment plans are available, as well as scholarship and funding options
  • You come out of the course with a recognized postgraduate degree

Payment and Enrollment

Though the course usually costs €6,500, OPIT offers “early bird” discounts that allow you to enroll for €4,950, assuming you sign up early enough. Intakes are semi-regular, with the next one scheduled for October 2023 and international students get 90 credits under the European Credit Transfer and Accumulation System (ECTS) for successful completion.

Tips for Success in an Applied AI Course

As you can see, you have plenty of options for applied AI courses, from professional certifications designed to get you into a career quickly to full postgraduate degrees. Regardless of your choice, these tips will help you get your precious certification:

  • Dedicate time for study – Time well managed is time well spent. Understand that you’ll need to dedicate self-learning time to get to grips with concepts you’re taught during classroom hours.
  • Set clear goals – Going into an applied AI course with no sense of what you’re supposed to get out of that course leaves you directionless upon completion. Make sure you know exactly what you stand to gain before committing time (and money) to a course.
  • Network often – Even online courses give you a chance to get involved in teamwork projects and speak to experienced industry professionals. Take those chances. The more connections you build during your studies, the more opportunities you’ll see coming out of the back end.
  • Seek guidance – As attractive as the prospect of self-guided learning may be, we all need a helping hand from time to time. If a course provides direct access to tutors and professors, use it.
  • Stay up to date – AI is a fast-moving field, with every change and advancement bringing new challenges and opportunities. Stay on top of what’s happening in the industry. You may just find that one course sets you up to be ready for those changes, while another may not.

Build Your Skills With an Applied AI Course

Whether you go down the full postgraduate degree route or you choose a professional qualification, an applied AI course is a route into one of the world’s fastest-growing industries. Simply put, we’re set for an AI explosion. Over the next decade, AI will permeate everything we do, from complex computing to simple office tasks, and you can use the right course to give yourself the skills you need to take advantage of that fact. Explore the options shared in this article, ask yourself what you want to achieve in your career, and make the educational choice that’s right for you.

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Master the AI Era: Key Skills for Success
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 24, 2025 6 min read

The world is rapidly changing. New technologies such as artificial intelligence (AI) are transforming our lives and work, redefining the definition of “essential office skills.”

So what essential skills do today’s workers need to thrive in a business world undergoing a major digital transformation? It’s a question that Alan Lerner, director at Toptal and lecturer at the Open Institute of Technology (OPIT), addressed in his recent online masterclass.

In a broad overview of the new office landscape, Lerner shares the essential skills leaders need to manage – including artificial intelligence – to keep abreast of trends.

Here are eight essential capabilities business leaders in the AI era need, according to Lerner, which he also detailed in OPIT’s recent Master’s in Digital Business and Innovation webinar.

An Adapting Professional Environment

Lerner started his discussion by quoting naturalist Charles Darwin.

“It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is the most adaptable to change.”

The quote serves to highlight the level of change that we are currently seeing in the professional world, said Lerner.

According to the World Economic Forum’s The Future of Jobs Report 2025, over the next five years 22% of the labor market will be affected by structural change – including job creation and destruction – and much of that change will be enabled by new technologies such as AI and robotics. They expect the displacement of 92 million existing jobs and the creation of 170 million new jobs by 2030.

While there will be significant growth in frontline jobs – such as delivery drivers, construction workers, and care workers – the fastest-growing jobs will be tech-related roles, including big data specialists, FinTech engineers, and AI and machine learning specialists, while the greatest decline will be in clerical and secretarial roles. The report also predicts that most workers can anticipate that 39% of their existing skill set will be transformed or outdated in five years.

Lerner also highlighted key findings in the Accenture Life Trends 2025 Report, which explores behaviors and attitudes related to business, technology, and social shifts. The report noted five key trends:

  • Cost of Hesitation – People are becoming more wary of the information they receive online.
  • The Parent Trap – Parents and governments are increasingly concerned with helping the younger generation shape a safe relationship with digital technology.
  • Impatience Economy – People are looking for quick solutions over traditional methods to achieve their health and financial goals.
  • The Dignity of Work – Employees desire to feel inspired, to be entrusted with agency, and to achieve a work-life balance.
  • Social Rewilding – People seek to disconnect and focus on satisfying activities and meaningful interactions.

These are consumer and employee demands representing opportunities for change in the modern business landscape.

Key Capabilities for the AI Era

Businesses are using a variety of strategies to adapt, though not always strategically. According to McClean & Company’s HR Trends Report 2025, 42% of respondents said they are currently implementing AI solutions, but only 7% have a documented AI implementation strategy.

This approach reflects the newness of the technology, with many still unsure of the best way to leverage AI, but also feeling the pressure to adopt and adapt, experiment, and fail forward.

So, what skills do leaders need to lead in an environment with both transformation and uncertainty? Lerner highlighted eight essential capabilities, independent of technology.

Capability 1: Manage Complexity

Leaders need to be able to solve problems and make decisions under fast-changing conditions. This requires:

  • Being able to look at and understand organizations as complex social-technical systems
  • Keeping a continuous eye on change and adopting an “outside-in” vision of their organization
  • Moving fast and fixing things faster
  • Embracing digital literacy and technological capabilities

Capability 2: Leverage Networks

Leaders need to develop networks systematically to achieve organizational goals because it is no longer possible to work within silos. Leaders should:

  • Use networks to gain insights into complex problems
  • Create networks to enhance influence
  • Treat networks as mutually rewarding relationships
  • Develop a robust profile that can be adapted for different networks

Capability 3: Think and Act “Global”

Leaders should benchmark using global best practices but adapt them to local challenges and the needs of their organization. This requires:

  • Identifying what great companies are achieving and seeking data to understand underlying patterns
  • Developing perspectives to craft global strategies that incorporate regional and local tactics
  • Learning how to navigate culturally complex and nuanced business solutions

Capability 4: Inspire Engagement

Leaders must foster a culture that creates meaningful connections between employees and organizational values. This means:

  • Understanding individual values and needs
  • Shaping projects and assignments to meet different values and needs
  • Fostering an inclusive work environment with plenty of psychological safety
  • Developing meaningful conversations and both providing and receiving feedback
  • Sharing advice and asking for help when needed

Capability 5: Communicate Strategically

Leaders should develop crisp, clear messaging adaptable to various audiences and focus on active listening. Achieving this involves:

  • Creating their communication style and finding their unique voice
  • Developing storytelling skills
  • Utilizing a data-centric and fact-based approach to communication
  • Continual practice and asking for feedback

Capability 6: Foster Innovation

Leaders should collaborate with experts to build a reliable innovation process and a creative environment where new ideas thrive. Essential steps include:

  • Developing or enhancing structures that best support innovation
  • Documenting and refreshing innovation systems, processes, and practices
  • Encouraging people to discover new ways of working
  • Aiming to think outside the box and develop a growth mindset
  • Trying to be as “tech-savvy” as possible

Capability 7: Cultivate Learning Agility

Leaders should always seek out and learn new things and not be afraid to ask questions. This involves:

  • Adopting a lifelong learning mindset
  • Seeking opportunities to discover new approaches and skills
  • Enhancing problem-solving skills
  • Reviewing both successful and unsuccessful case studies

Capability 8: Develop Personal Adaptability

Leaders should be focused on being effective when facing uncertainty and adapting to change with vigor. Therefore, leaders should:

  • Be flexible about their approach to facing challenging situations
  • Build resilience by effectively managing stress, time, and energy
  • Recognize when past approaches do not work in current situations
  • Learn from and capitalize on mistakes

Curiosity and Adaptability

With the eight key capabilities in mind, Lerner suggests that curiosity and adaptability are the key skills that everyone needs to thrive in the current environment.

He also advocates for lifelong learning and teaches several key courses at OPIT which can lead to a Bachelor’s Degree in Digital Business.

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Lessons From History: How Fraud Tactics From the 18th Century Still Impact Us Today
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 17, 2025 6 min read

Many people treat cyber threats and digital fraud as a new phenomenon that only appeared with the development of the internet. But fraud – intentional deceit to manipulate a victim – has always existed; it is just the tools that have changed.

In a recent online course for the Open Institute of Technology (OPIT), AI & Cybersecurity Strategist Tom Vazdar, chair of OPIT’s Master’s Degree in Enterprise Cybersecurity, demonstrated the striking parallels between some of the famous fraud cases of the 18th century and modern cyber fraud.

Why does the history of fraud matter?

Primarily because the psychology and fraud tactics have remained consistent over the centuries. While cybersecurity is a tool that can combat modern digital fraud threats, no defense strategy will be successful without addressing the underlying psychology and tactics.

These historical fraud cases Vazdar addresses offer valuable lessons for current and future cybersecurity approaches.

The South Sea Bubble (1720)

The South Sea Bubble was one of the first stock market crashes in history. While it may not have had the same far-reaching consequences as the Black Thursday crash of 1929 or the 2008 crash, it shows how fraud can lead to stock market bubbles and advantages for insider traders.

The South Sea Company was a British company that emerged to monopolize trade with the Spanish colonies in South America. The company promised investors significant returns but provided no evidence of its activities. This saw the stock prices grow from £100 to £1,000 in a matter of months, then crash when the company’s weakness was revealed.

Many people lost a significant amount of money, including Sir Isaac Newton, prompting the statement, “I can calculate the movement of the stars, but not the madness of men.

Investors often have no way to verify a company’s claim, making stock markets a fertile ground for manipulation and fraud since their inception. When one party has more information than another, it creates the opportunity for fraud. This can be seen today in Ponzi schemes, tech stock bubbles driven by manipulative media coverage, and initial cryptocurrency offerings.

The Diamond Necklace Affair (1784-1785)

The Diamond Necklace Affair is an infamous incident of fraud linked to the French Revolution. An early example of identity theft, it also demonstrates that the harm caused by such a crime can go far beyond financial.

A French aristocrat named Jeanne de la Mont convinced Cardinal Louis-René-Édouard, Prince de Rohan into thinking that he was buying a valuable diamond necklace on behalf of Queen Marie Antoinette. De la Mont forged letters from the queen and even had someone impersonate her for a meeting, all while convincing the cardinal of the need for secrecy. The cardinal overlooked several questionable issues because he believed he would gain political benefit from the transaction.

When the scheme finally exposed, it damaged Marie Antoinette’s reputation, despite her lack of involvement in the deception. The story reinforced the public perception of her as a frivolous aristocrat living off the labor of the people. This contributed to the overall resentment of the aristocracy that erupted in the French Revolution and likely played a role in Marie Antoinette’s death. Had she not been seen as frivolous, she might have been allowed to live after her husband’s death.

Today, impersonation scams work in similar ways. For example, a fraudster might forge communication from a CEO to convince employees to release funds or take some other action. The risk of this is only increasing with improved technology such as deepfakes.

Spanish Prisoner Scam (Late 1700s)

The Spanish Prisoner Scam will probably sound very familiar to anyone who received a “Nigerian prince” email in the early 2000s.

Victims received letters from a “wealthy Spanish prisoner” who needed their help to access his fortune. If they sent money to facilitate his escape and travel, he would reward them with greater riches when he regained his fortune. This was only one of many similar scams in the 1700s, often involving follow-up requests for additional payments before the scammer disappeared.

While the “Nigerian prince” scam received enough publicity that it became almost unbelievable that people could fall for it, if done well, these can be psychologically sophisticated scams. The stories play on people’s emotions, get them invested in the person, and enamor them with the idea of being someone helpful and important. A compelling narrative can diminish someone’s critical thinking and cause them to ignore red flags.

Today, these scams are more likely to take the form of inheritance fraud or a lottery scam, where, again, a person has to pay an advance fee to unlock a much bigger reward, playing on the common desire for easy money.

Evolution of Fraud

These examples make it clear that fraud is nothing new and that effective tactics have thrived over the centuries. Technology simply opens up new opportunities for fraud.

While 18th-century scammers had to rely on face-to-face contact and fraudulent letters, in the 19th century they could leverage the telegraph for “urgent” communication and newspaper ads to reach broader audiences. In the 20th century, there were telephones and television ads. Today, there are email, social media, and deepfakes, with new technologies emerging daily.

Rather than quack doctors offering miracle cures, we see online health scams selling diet pills and antiaging products. Rather than impersonating real people, we see fake social media accounts and catfishing. Fraudulent sites convince people to enter their bank details rather than asking them to send money. The anonymity of the digital world protects perpetrators.

But despite the technology changing, the underlying psychology that makes scams successful remains the same:

  • Greed and the desire for easy money
  • Fear of missing out and the belief that a response is urgent
  • Social pressure to “keep up with the Joneses” and the “Bandwagon Effect”
  • Trust in authority without verification

Therefore, the best protection against scams remains the same: critical thinking and skepticism, not technology.

Responding to Fraud

In conclusion, Vazdar shared a series of steps that people should take to protect themselves against fraud:

  • Think before you click.
  • Beware of secrecy and urgency.
  • Verify identities.
  • If it seems too good to be true, be skeptical.
  • Use available security tools.

Those security tools have changed over time and will continue to change, but the underlying steps for identifying and preventing fraud remain the same.

For more insights from Vazdar and other experts in the field, consider enrolling in highly specialized and comprehensive programs like OPIT’s Enterprise Security Master’s program.

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