

Once a concept found exclusively in science fiction, machine learning has seen widespread use in the modern age. As soon as various industries grasped the potential of ML, this field of computer science turned into a staple of tech and other businesses.
Naturally, all this has led to an increased demand for machine learning experts. The job market abounds with offers for positions in the field, and the competition is fierce. In other words, you may find plenty of job openings for machine learning professionals, but you’ll need to fit the bill to actually land the position.
Fortunately, there are plenty of online machine learning courses to give you the needed expertise and boost your skills. This article will help you find the best machine learning course online and explain the top options in detail.
Factors to Consider When Choosing an Online Machine Learning Course
If you like the idea of online learning, machine learning courses are readily available. In fact, the number of options may be overwhelming. That’s why we’ve applied certain strict criteria when looking for the best machine learning online course. Moving forward, you should also keep those criteria in mind.
Firstly, the content of the course will matter the most. Machine learning is a broad field, and you’ll want to ensure that the education you’re getting is the one you need. Also, every genuine venue of machine learning online training should give you a solid foundation while placing a particular emphasis to specific skills.
The curriculum won’t be the only aspect of the course that matters, though. Who is teaching you will be crucial as well. Ideally, your instructor should be an experienced professional in the field so that they can teach you the theory as well as the practical applications.
Next, one of the primary reasons why you’d want to take a course rather than enroll into a BSc or MSc program is time. You don’t want a course to take up too much of your time, which is why flexibility and the overall duration are essential. You’ll want a well-structured online machine learning course that will leave room for a job or any other activities.
Beside the knowledge provided, hands-on experience will be vital. Once you complete a course, you should be able to apply everything you’ve learned there. To that end, a quality machine learning online course will focus heavily on the real-world application of the skills taught.
Finally, the pricing will play a major role. Similar to time, budgetary concerns are likely a core reason why you’re opting for a course. Simply put, you don’t want it to cost the same as a year at a university. And if the price is somewhat higher, the course should provide plenty of additional resources to justify it.
Top Online Machine Learning Courses
Imperial College Business School – Professional Certificate in Machine Learning and Artificial Intelligence
Course Overview
This program deals with the essential AI and machine learning concepts, teaching you when and how ML solutions can be applied to real-life problems. The course is relatively long, lasting for 25 weeks. It was developed in collaboration with the Imperial College’s Department of Computing.
Key Features
- Taught by experts
- Hands-on activities
- Projects worthy of your portfolio
- Ends with a capstone project
- Verified digital certificate
Pricing and Additional Resources
The price of this course is £3,995, which is reasonable considering its extended duration. During the course, you’ll have individual advisor support for career-building. Completing your studies will also grant you the status of an Associate Alumni, allowing you to join the Imperial College Business School’s community.
Google Digital Garage – Machine Learning Crash Course
Course Overview
If you want to learn machine learning fundamentals quickly and efficiently, this course is just the ticket. It includes comprehensive text and video lectures, practical exercises, and work with the TensorFlow ML library. You’ll gain relevant knowledge and experience through three modules lasting a total of 15 hours.
Key Features
- Lecturers are Google’s researchers
- Intermediate level
- Genuine case studies
- Interactive algorithm showcases
- Fast-paced and applicable
Pricing and Additional Resources
If you’re wondering how much a course from a leading tech giant company may cost, you’ll be pleasantly surprised: This Google machine learning online course is absolutely free. In addition, it’s quite short and very efficient.
IBM (via edX) – Machine Learning With Python: A Practical Introduction
Course Overview
This course teaches you supervised and unsupervised machine learning using Python. An introductory course, it may last up to five weeks. Best of all, the program is entirely self-paced, meaning you can tackle individual lessons at a tempo that suits you. It’s worth noting that this course also explores widely used models and algorithms, supported by actual examples.
Key Features
- Taught by a Senior Data Scientists at IBM
- Part of IBM’s one year certificate program for data science professionals
- Beginner-friendly
- Focus on statistics and data analysis
Pricing and Additional Resources
Like Google’s course, this program by IBM, hosted on edX, is free. It’s worth noting that there’s also a “Verified Track” version, priced on edX at $99. This version of the course will provide unlimited source material access, exams, graded assignments, and a shareable certificate.
DeepLearning.AI (via Coursera) – Unsupervised Learning, Recommenders, Reinforcement Learning
Course Overview
As a part of a specialization in machine learning, this course teaches unsupervised learning as a particular branch of ML. You’ll also learn about recommender systems and how to build certain machine learning models. The course is designed by experienced DeepLearning.AI members in collaboration with Stanford University. You’ll be able to complete it in about 27 hours.
Key Features
- Flexible course scheduling
- Part of a three-course specialization
- Taught by an experienced lecturer and ML professional
- Beginner-friendly
- Teaches specific machine learning techniques
Pricing and Additional Resources
This course, as well as the entire specialization, is available with a Coursera subscription. As a subscriber, you won’t pay any additional fees for the course. Plus, you’ll gain access to a shareable certificate, practice and graded quizzes, and other subscriber benefits.
Microsoft – Foundations of Data Science for Machine Learning
Course Overview
More than a regular course, Foundations of Data Science for Machine Learning is a learning path which consists of 14 modules. It will take you through the entire journey, from the machine learning basics to advanced architecture and data analysis. The course can be completed in under 13 hours.
Key Features
- Offered by a leading tech giant
- Provides lessons and exercises
- Entirely browser-based
- Interactive learning
Pricing and Additional Resources
This training course by Microsoft is free and available immediately. Enrolling in the course comes with no prerequisites.
Tips for Success in Online Machine Learning Courses
Once you choose a machine learning online course, simply signing up for it won’t be enough. You’ll want to ensure you’re getting the most value out of the program. To that end, it would be best to apply the following tips:
- Set your goals and expectations: The best way to get optimal results from a course is to go into it knowing precisely what you want. Clarify what you’re looking to achieve and what you expect the course to provide, and you’ll have an easier time both choosing and completing the program.
- Dedicate time to study and practice: Course lectures will be a vital part of the learning process, but the time and work you put into it will be what makes it all worthwhile. Approach your machine learning online course with the utmost dedication and responsibility, making sure to always set aside the time of day for studying.
- Engage with the community: A learning environment is perfect for building a network. You’ll contact other people with similar interests, which may broaden your viewpoint, provide additional knowledge, and even open up job opportunities. Don’t shy away from online forums or any other type of meeting place that your peers frequent.
- Try out new skills and concepts in real-life: Even if the course you pick involves practical projects, you should be proactive beyond that point. Take what you’ve learned and try to apply it on something outside the course. The best time to start practicing is as soon as you learn a new skill.
- Keep updating your knowledge and skills: Machine learning progresses rapidly, so you’ll have to do your best in keeping your knowledge and skills relevant. A quality course will give you a good foundation. However, updating what you’ve learned will be entirely up to you.
Become a Machine Learning Expert Online
If you’ve found the best machine learning course online for your purposes, you should start learning right away. Armed with the proper skills, you’ll have greater chances of getting work in the industry and starting a career in this science of the future.
Explore which machine learning online course fits you best and start pursuing your goals. You’ll find the knowledge and experience gained as the perfect catalysts for personal and professional growth.
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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.

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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