If we think of “computer science” as an umbrella term for so many aspects of computing today, its importance is immediately apparent. Artificial intelligence (and the programming that lies behind it) falls into the computer science category. The same goes for machine learning, data science, networking, cybersecurity, and so many other elements of what make modern computing technology tick.

You need a solid grounding in computer science – both general concepts and theory – to move into one of these areas of specialization. And if you need to get that grounding on a budget, these free computer science courses teach you what you need to know and come with a handy certification.

Top Free Certified Computer Science Online Courses

As surprising as it may seem, you don’t have to pay money to get an education in computer science that employers actually care about. Free courses exist. And many of these free online computer science courses deliver a certification that proves your knowledge and comes from an institution that employers respect.

Course 1 – CS50: Introduction to Computer Science (Harvard University)

We’re stretching the definition of “free and certified” with the first course on the list. Though it’s free to take (and you get an audit of your performance without paying a penny), the verified certification for Harvard’s CS50 course costs $189 (approx. €175).

Assuming you’re willing to part with the cash, this course gives you a certificate from one of the United States’ most respected institutions, in addition to a crash course in computer science fundamentals. Over 11 weeks of self-paced learning (you’ll need to commit at least 10 hours per week to the course) you’ll develop a fundamental understanding of computer science and the programming that underpins it.

Concepts covered include data structures, abstraction, web development, and algorithms, creating a course that melds the math of modern computing with the theoretical concepts you’ll apply in the real world. Prospective programmers enjoy some diversity, too, as the course teaches the basics of several languages. Python, C, JavaScript, and HTML are all covered, though not in enough detail for you to achieve mastery in any of them. Still, as online certified courses for computer science go, CS50 delivers a prestigious certificate and exposes you to ambitious peers who may offer networking potential beyond the course content.

Course 2 – CS50’s Computer Science for Business Professionals (Harvard University)

It’s hard to look beyond Harvard when it comes to free computer science courses because you’re getting education and certification from a top university. With CS50 Computer Science for Business Professionals, Harvard moves beyond the tech-centric approach of its usual CS50 course to demonstrate how computer science principles apply in a real-world setting.

It’s a short course, clocking in at six weeks of study and only requiring two-to-six hours of work per week. That makes it perfect for professionals who want to boost their knowledge without a full-time commitment. You’ll tackle more high-level concepts in computer science, including the fundamentals of cloud computing and how to build technology stacks. All of which makes this like a speed run through of what you need to know about computing on a business level.

That’s not to say you won’t learn any technical theory. Several programming languages are covered (albeit in short-form style), as are the basics of computational thinking. But like CS50 above, certification comes at a cost, even if the course itself is free. Paying for an optional upgrade with EDX (through which the course is offered) is the only way to nab your certificate, if you do get a free course audit to demonstrate completion regardless.

Course 3 – Introduction to Computer Science and Programming Using Python (Massachusetts Institute of Technology)

Offered in conjunction with the EDX platform, this computer science online course takes a Python-focused approach to its teaching. Unlike CS50, which covers a wide range of topics in brief, MIT’s course focuses on how computer science is like a tool that you can use to create software and algorithms. Python 3.5 is the technology behind that tool and you’ll learn how to use it by examining and analyzing real-world problems.

The nine-week course starts by demonstrating the basics of Python (some self-learning and expansion of these concepts may be required) before moving into algorithms. Once you’ve gotten to grips with basic algorithm creation, you’ll learn how to test what you create and how those algorithms become the building blocks of complex data structures.

You have to make a substantial time commitment with this course, with MIT requiring you to spend at least 14 hours per week on your studies if you wish to stick to the nine-week schedule. And though effective in teaching you the basics of Python, the course is really a primer for a second MIT course – Introduction to Computational Thinking and Data Science – that requires payment. But it’s a useful course as a standalone product, but you’ll have to pay a fee to EDX if you want a course-centric certificate.

Factors to Consider When Choosing a Free Certified Computer Science Online Course

The trio of free online computer science courses discussed above each offer something different. Depending on your choice, you’ll get a bottom-up crash course in the theory, a practical understanding of how computer science works in a business context, or an in-depth guide to using Python. But when choosing between the three courses above (or any other courses you find) you must consider the following factors.

The Course Content and Its Relevance to Your Goals

The big question here is – what do you want to achieve with the course?

Sure, having a certificate, especially one with a major university’s name on it, is nice. But if that certificate demonstrates that you’ve learned skills that you don’t need for your intended career path then it’s not worth the paper it’s printed on.

Think of choosing a course like making an investment on which you expect a return. Outline your goals – both learning-centric and career-based – for taking the course. Then, find a course that helps you to reach those goals through laser-focused learning on topics you’ll use in the future.

Course Duration and Flexibility

For a young learner without full-time work or family commitments, taking on a computer science online course that requires months of study may not be a big deal. But that’s not the case for everybody. If you have limited hours available during the week, you need a course that you can fit into those hours rather than one that forces you to fit your life around the course.

Thankfully, most free online computer science courses make allowances for schedule flexibility by taking a self-paced learning approach. You’ll get access to all of the course resources upfront, allowing you to choose when you study. You may be able to get ahead during one week in preparation for a week where you know you can’t commit as much time, giving you the flexibility you need to fit the course into your schedule.

The Instructors and Their Expertise

Would you want to learn the theory of how to pilot a plane from somebody who’s never been up in the air? Of course you wouldn’t, and you must adopt the same attitude when choosing a computer science course.

Check the faculty list associated with the course (most reputable courses tell you who created them) and dig into their individual credentials. What have they done in the computer science industry? Where did they learn what they know? The answers to these questions tell you if your instructors and, by extension, your course are credible.

The Value of the Certification

When it comes to certification, look beyond the website that offers the course and instead focus on the institution that created it. For example, CS50’s Computer Science for Business Professionals is offered via the EDX platform, which doesn’t mean much to potential employers. But that certificate comes with a stamp of approval from Harvard University, which is a school that’s going to immediately raise eyebrows if it’s on your CV.

The point is that reputation matters, though it’s the reputation of the course creator that matters above that of the course platform. The more prestigious the name on the piece of paper, the more valuable the certificate is in the eyes of employers.

Tips for Successfully Completing a Free Certified Computer Science Online Course

With the tips for sifting through the sands of free computer science courses established, let’s round things off with some quick tips that’ll help you succeed in your studies:

  • Set clear goals for your education from the outset, with those goals aligning with your current experience level and desired outcomes.
  • Create a study schedule that fits around your commitments and stick to it as closely as you can.
  • Don’t skip assignments or practical sessions because everything included in the course is there to teach you something valuable.
  • Engage with the course community both to get advice from your peers and to potentially create networking opportunities.
  • Dedicate time to revision and research when preparing for exams or practical assessments to ensure you fully understand the course content.

Get Certified for Free and Improve Your Job Prospects

Given the importance of computer science to modern business – even the simplest of companies use software and have networks – it’s reasonable to want to build your knowledge of the subject. Free online computer science courses allow you to do that in exchange for a time commitment, with many allowing you to inject some flexibility into your study schedule.

Explore the three courses highlighted here, and look beyond them to more specialized courses once you’re confident in the foundational knowledge you’ve built. And remember – even a certificate from a free course has value in the job market if that course was created by a recognized institution.

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Sage: The ethics of AI: how to ensure your firm is fair and transparent
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Mar 7, 2025 3 min read

Source:


By Chris Torney

Artificial intelligence (AI) and machine learning have the potential to offer significant benefits and opportunities to businesses, from greater efficiency and productivity to transformational insights into customer behaviour and business performance. But it is vital that firms take into account a number of ethical considerations when incorporating this technology into their business operations. 

The adoption of AI is still in its infancy and, in many countries, there are few clear rules governing how companies should utilise the technology. However, experts say that firms of all sizes, from small and medium-sized businesses (SMBs) to international corporations, need to ensure their implementation of AI-based solutions is as fair and transparent as possible. Failure to do so can harm relationships with customers and employees, and risks causing serious reputational damage as well as loss of trust.

What are the main ethical considerations around AI?

According to Pierluigi Casale, professor in AI at the Open Institute of Technology, the adoption of AI brings serious ethical considerations that have the potential to affect employees, customers and suppliers. “Fairness, transparency, privacy, accountability, and workforce impact are at the core of these challenges,” Casale explains. “Bias remains one of AI’s biggest risks: models trained on historical data can reinforce discrimination, and this can influence hiring, lending and decision-making.”

Part of the problem, he adds, is that many AI systems operate as ‘black boxes’, which makes their decision-making process hard to understand or interpret. “Without clear explanations, customers may struggle to trust AI-driven services; for example, employees may feel unfairly assessed when AI is used for performance reviews.”

Casale points out that data privacy is another major concern. “AI relies on vast datasets, increasing the risk of breaches or misuse,” he says. “All companies operating in Europe must comply with regulations such as GDPR and the AI Act, ensuring responsible data handling to protect customers and employees.”

A third significant ethical consideration is the potential impact of AI and automation on current workforces. Businesses may need to think about their responsibilities in terms of employees who are displaced by technology, for example by introducing training programmes that will help them make the transition into new roles.

Olivia Gambelin, an AI ethicist and the founder of advisory network Ethical Intelligence, says the AI-related ethical considerations are likely to be specific to each business and the way it plans to use the technology. “It really does depend on the context,” she explains. “You’re not going to find a magical checklist of five things to consider on Google: you actually have to do the work, to understand what you are building.”

This means business leaders need to work out how their organisation’s use of AI is going to impact the people – the customers and employees – that come into contact with it, Gambelin says. “Being an AI-enabled company means nothing if your employees are unhappy and fearful of their jobs, and being an AI-enabled service provider means nothing if it’s not actually connecting with your customers.”

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Reuters: EFG Watch: DeepSeek poses deep questions about how AI will develop
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Feb 10, 2025 4 min read

Source:

  • Reuters, Published on February 10th, 2025.

By Mike Scott

Summary

  • DeepSeek challenges assumptions about AI market and raises new ESG and investment risks
  • Efficiency gains significant – similar results being achieved with less computing power
  • Disruption fuels doubts over Big Tech’s long-term AI leadership and market valuations
  • China’s lean AI model also casts doubt on costly U.S.-backed Stargate project
  • Analysts see DeepSeek as a counter to U.S. tariffs, intensifying geopolitical tensions

February 10 – The launch by Chinese company DeepSeek, opens new tab of its R1 reasoning model last month caused chaos in U.S. markets. At the same time, it shone a spotlight on a host of new risks and challenged market assumptions about how AI will develop.

The shock has since been overshadowed by President Trump’s tariff wars, opens new tab, but DeepSeek is set to have lasting and significant implications, observers say. It is also a timely reminder of why companies and investors need to consider ESG risks, and other factors such as geopolitics, in their investment strategies.

“The DeepSeek saga is a fascinating inflection point in AI’s trajectory, raising ESG questions that extend beyond energy and market concentration,” Peter Huang, co-founder of Openware AI, said in an emailed response to questions.

DeepSeek put the cat among the pigeons by announcing that it had developed its model for around $6 million, a thousandth of the cost of some other AI models, while also using far fewer chips and much less energy.

Camden Woollven, group head of AI product marketing at IT governance and compliance group GRC International, said in an email that “smaller companies and developers who couldn’t compete before can now get in the game …. It’s like we’re seeing a democratisation of AI development. And the efficiency gains are significant as they’re achieving similar results with much less computing power, which has huge implications for both costs and environmental impact.”

The impact on AI stocks and companies associated with the sector was severe. Chipmaker Nvidia lost almost $600 billion in market capitalisation after the DeepSeek announcement on fears that demand for its chips would be lower, but there was also a 20-30% drop in some energy stocks, said Stephen Deadman, UK associate partner at consultancy Sia.

As Reuters reported, power producers were among the biggest winners in the S&P 500 last year, buoyed by expectations of ballooning demand from data centres to scale artificial intelligence technologies, yet they saw the biggest-ever one-day drops after the DeepSeek announcement.

One reason for the massive sell-off was the timing – no-one was expecting such a breakthrough, nor for it to come from China. But DeepSeek also upended the prevailing narrative of how AI would develop, and who the winners would be.

Tom Vazdar, professor of cybersecurity and AI at Open Institute of Technology (OPIT), pointed out in an email that it called into question the premise behind the Stargate Project,, opens new tab a $500 billion joint venture by OpenAI, SoftBank and Oracle to build AI infrastructure in the U.S., which was announced with great fanfare by Donald Trump just days before DeepSeek’s announcement.

“Stargate has been premised on the notion that breakthroughs in AI require massive compute and expensive, proprietary infrastructure,” Vazdar said in an email.

There are also dangers in markets being dominated by such a small group of tech companies. As Abbie Llewellyn-Waters, Investment manager at Jupiter Asset Management, pointed out in a research note, the “Magnificent Seven” tech stocks had accounted for nearly 60% of the index’s gains over the previous two years. The group of mega-caps comprised more than a third of the S&P 500’s total value in December 2024.

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