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.
Related posts
Source:
- The Yuan, Published on October 25th, 2024.
By Zorina Alliata
Artificial intelligence is a classic example of a mismatch between perceptions and reality, as people tend to overlook its positive aspects and fear it far more than what is warranted by its actual capabilities, argues AI strategist and professor Zorina Alliata.
ALEXANDRIA, VIRGINIA – In recent years, artificial intelligence (AI) has grown and developed into something much bigger than most people could have ever expected. Jokes about robots living among humans no longer seem so harmless, and the average person began to develop a new awareness of AI and all its uses. Unfortunately, however – as is often a human tendency – people became hyper-fixated on the negative aspects of AI, often forgetting about all the good it can do. One should therefore take a step back and remember that humanity is still only in the very early stages of developing real intelligence outside of the human brain, and so at this point AI is almost like a small child that humans are raising.
AI is still developing, growing, and adapting, and like any new tech it has its drawbacks. At one point, people had fears and doubts about electricity, calculators, and mobile phones – but now these have become ubiquitous aspects of everyday life, and it is not difficult to imagine a future in which this is the case for AI as well.
The development of AI certainly comes with relevant and real concerns that must be addressed – such as its controversial role in education, the potential job losses it might lead to, and its bias and inaccuracies. For every fear, however, there is also a ray of hope, and that is largely thanks to people and their ingenuity.
Looking at education, many educators around the world are worried about recent developments in AI. The frequently discussed ChatGPT – which is now on its fourth version – is a major red flag for many, causing concerns around plagiarism and creating fears that it will lead to the end of writing as people know it. This is one of the main factors that has increased the pessimistic reporting about AI that one so often sees in the media.
However, when one actually considers ChatGPT in its current state, it is safe to say that these fears are probably overblown. Can ChatGPT really replace the human mind, which is capable of so much that AI cannot replicate? As for educators, instead of assuming that all their students will want to cheat, they should instead consider the options for taking advantage of new tech to enhance the learning experience. Most people now know the tell-tale signs for identifying something that ChatGPT has written. Excessive use of numbered lists, repetitive language and poor comparison skills are just three ways to tell if a piece of writing is legitimate or if a bot is behind it. This author personally encourages the use of AI in the classes I teach. This is because it is better for students to understand what AI can do and how to use it as a tool in their learning instead of avoiding and fearing it, or being discouraged from using it no matter the circumstances.
Educators should therefore reframe the idea of ChatGPT in their minds, have open discussions with students about its uses, and help them understand that it is actually just another tool to help them learn more efficiently – and not a replacement for their own thoughts and words. Such frank discussions help students develop their critical thinking skills and start understanding their own influence on ChatGPT and other AI-powered tools.
By developing one’s understanding of AI’s actual capabilities, one can begin to understand its uses in everyday life. Some would have people believe that this means countless jobs will inevitably become obsolete, but that is not entirely true. Even if AI does replace some jobs, it will still need industry experts to guide it, meaning that entirely new jobs are being created at the same time as some older jobs are disappearing.
Adapting to AI is a new challenge for most industries, and it is certainly daunting at times. The reality, however, is that AI is not here to steal people’s jobs. If anything, it will change the nature of some jobs and may even improve them by making human workers more efficient and productive. If AI is to be a truly useful tool, it will still need humans. One should remember that humans working alongside AI and using it as a tool is key, because in most cases AI cannot do the job of a person by itself.
Is AI biased?
Why should one view AI as a tool and not a replacement? The main reason is because AI itself is still learning, and AI-powered tools such as ChatGPT do not understand bias. As a result, whenever ChatGPT is asked a question it will pull information from anywhere, and so it can easily repeat old biases. AI is learning from previous data, much of which is biased or out of date. Data about home ownership and mortgages, e.g., are often biased because non-white people in the United States could not get a mortgage until after the 1960s. The effect on data due to this lending discrimination is only now being fully understood.
AI is certainly biased at times, but that stems from human bias. Again, this just reinforces the need for humans to be in control of AI. AI is like a young child in that it is still absorbing what is happening around it. People must therefore not fear it, but instead guide it in the right direction.
For AI to be used as a tool, it must be treated as such. If one wanted to build a house, one would not expect one’s tools to be able to do the job alone – and AI must be viewed through a similar lens. By acknowledging this aspect of AI and taking control of humans’ role in its development, the world would be better placed to reap the benefits and quash the fears associated with AI. One should therefore not assume that all the doom and gloom one reads about AI is exactly as it seems. Instead, people should try experimenting with it and learning from it, and maybe soon they will realize that it was the best thing that could have happened to humanity.
Read the full article below:
Source:
- The European Business Review, Published on October 27th, 2024.
By Lokesh Vij
Lokesh Vij is a Professor of BSc in Modern Computer Science & MSc in Applied Data Science & AI at Open Institute of Technology. With over 20 years of experience in cloud computing infrastructure, cybersecurity and cloud development, Professor Vij is an expert in all things related to data and modern computer science.
In today’s rapidly evolving technological landscape, the fields of blockchain and cloud computing are transforming industries, from finance to healthcare, and creating new opportunities for innovation. Integrating these technologies into education is not merely a trend but a necessity to equip students with the skills they need to thrive in the future workforce. Though both technologies are independently powerful, their potential for innovation and disruption is amplified when combined. This article explores the pressing questions surrounding the inclusion of blockchain and cloud computing in education, providing a comprehensive overview of their significance, benefits, and challenges.
The Technological Edge and Future Outlook
Cloud computing has revolutionized how businesses and individuals’ access and manage data and applications. Benefits like scalability, cost efficiency (including eliminating capital expenditure – CapEx), rapid innovation, and experimentation enable businesses to develop and deploy new applications and services quickly without the constraints of traditional on-premises infrastructure – thanks to managed services where cloud providers manage the operating system, runtime, and middleware, allowing businesses to focus on development and innovation. According to Statista, the cloud computing market is projected to reach a significant size of Euro 250 billion or even higher by 2028 (from Euro 110 billion in 2024), with a substantial Compound Annual Growth Rate (CAGR) of 22.78%. The widespread adoption of cloud computing by businesses of all sizes, coupled with the increasing demand for cloud-based services and applications, fuels the need for cloud computing professionals.
Blockchain, a distributed ledger technology, has paved the way by providing a secure, transparent, and tamper-proof way to record transactions (highly resistant to hacking and fraud). In 2021, European blockchain startups raised $1.5 billion in funding, indicating strong interest and growth potential. Reports suggest the European blockchain market could reach $39 billion by 2026, with a significant CAGR of over 47%. This growth is fueled by increasing adoption in sectors like finance, supply chain, and healthcare.
Addressing the Skills Gap
Reports from the World Economic Forum indicate that 85 million jobs may be displaced by a shift in the division of labor between humans and machines by 2025. However, 97 million new roles may emerge that are more adapted to the new division of labor between humans, machines, and algorithms, many of which will require proficiency in cloud computing and blockchain.
Furthermore, the World Economic Forum predicts that by 2027, 10% of the global GDP will be tokenized and stored on the blockchain. This massive shift means a surge in demand for blockchain professionals across various industries. Consider the implications of 10% of the global GDP being on the blockchain: it translates to a massive need for people who can build, secure, and manage these systems. We’re talking about potentially millions of jobs worldwide.
The European Blockchain Services Infrastructure (EBSI), an EU initiative, aims to deploy cross-border blockchain services across Europe, focusing on areas like digital identity, trusted data sharing, and diploma management. The EU’s MiCA (Crypto-Asset Regulation) regulation, expected to be fully implemented by 2025, will provide a clear legal framework for crypto-assets, fostering innovation and investment in the blockchain space. The projected growth and supportive regulatory environment point to a rising demand for blockchain professionals in Europe. Developing skills related to EBSI and its applications could be highly advantageous, given its potential impact on public sector blockchain adoption. Understanding the MiCA regulation will be crucial for blockchain roles related to crypto-assets and decentralized finance (DeFi).
Furthermore, European businesses are rapidly adopting digital technologies, with cloud computing as a core component of this transformation. GDPR (Data Protection Regulations) and other data protection laws push businesses to adopt secure and compliant cloud solutions. Many European countries invest heavily in cloud infrastructure and promote cloud adoption across various sectors. Artificial intelligence and machine learning will be deeply integrated into cloud platforms, enabling smarter automation, advanced analytics, and more efficient operations. This allows developers to focus on building applications without managing servers, leading to faster development cycles and increased scalability. Processing data closer to the source (like on devices or local servers) will become crucial for applications requiring real-time responses, such as IoT and autonomous vehicles.
The projected growth indicates a strong and continuous demand for blockchain and cloud professionals in Europe and worldwide. As we stand at the “crossroads of infinity,” there is a significant skill shortage, which will likely increase with the rapid adoption of these technologies. A 2023 study by SoftwareOne found that 95% of businesses globally face a cloud skills gap. Specific skills in high demand include cloud security, cloud-native development, and expertise in leading cloud platforms like AWS, Azure, and Google Cloud. The European Commission’s Digital Economy and Society Index (DESI) highlights a need for improved digital skills in areas like blockchain to support the EU’s digital transformation goals. A 2023 report by CasperLabs found that 90% of businesses in the US, UK, and China adopt blockchain, but knowledge gaps and interoperability challenges persist.
The Role of Educational Institutions
This surge in demand necessitates a corresponding increase in qualified individuals who can design, implement, and manage cloud-based and blockchain solutions. Educational institutions have a critical role to play in bridging this widening skills gap and ensuring a pipeline of talent ready to meet the demands of this burgeoning industry.
To effectively prepare the next generation of cloud computing and blockchain experts, educational institutions need to adopt a multi-pronged approach. This includes enhancing curricula with specialized programs, integrating cloud and blockchain concepts into existing courses, and providing hands-on experience with leading technology platforms.
Furthermore, investing in faculty development to ensure they possess up-to-date knowledge and expertise is crucial. Collaboration with industry partners through internships, co-teach programs, joint research projects, and mentorship programs can provide students with invaluable real-world experience and insights.
Beyond formal education, fostering a culture of lifelong learning is essential. Offering continuing education courses, boot camps, and online resources enables professionals to upskill or reskill and stay abreast of the latest advancements in cloud computing. Actively promoting awareness of career paths and opportunities in this field and facilitating connections with potential employers can empower students to thrive in the dynamic and evolving landscape of cloud computing and blockchain technologies.
By taking these steps, educational institutions can effectively prepare the young generation to fill the skills gap and thrive in the rapidly evolving world of cloud computing and blockchain.
Read the full article below:
Have questions?
Visit our FAQ page or get in touch with us!
Write us at +39 335 576 0263
Get in touch at hello@opit.com
Talk to one of our Study Advisors
We are international
We can speak in: