Data science is likely the most sought-after profession today. With top tech organizations looking for talent across the world, this field is highly competitive. That’s why professional improvement represents a crucial aspect of this rapidly-evolving industry.

Getting an approved certificate is the best way to gain the necessary knowledge and a confirmation of your data science skills. This article will give you a list of the 10 best online courses and data science certificate programs that offer worldwide recognized certification.

Factors to Consider When Choosing a Data Science Certification Course

There’s plenty of criteria to look at when choosing a data science certification course online. Of course, the content of the course will be of most interest, especially since data science is a broad field. But several other aspects are also worth researching:

  • Program duration
  • Flexibility – is it on a fixed timeline or self-paced
  • Instructor quality and the reputation of the institution
  • Pricing
  • Whether the program offers practical projects and hands-on work
  • Whether the institution will help you land your next job

Top 10 Online Data Science Certification Courses & Programs

Here’s a brief overview of what the top online courses in data science have to offer. Courses and programs on our list come from respected institutions that hire world-class lecturers and will provide the best certification for data science you could get without setting foot on campus.

Harvard University – Professional Certificate in Data Science

Getting an education in data science from Harvard University is one of the best options in the market. This online course teaches essential skills in programming, modeling, statistics, data visualization, and numerous data science tools.

The Professional Certificate in Data Science course is self-paced and represents an introductory course tailored for beginners who want to advance their skills. You’ll also learn through relevant case studies by analyzing data from real-life examples. The program includes working in the R environment.

The price of this Harvard program is $991, with an available 10% discount. The course runs through the edX platform, and allows you free access to the entire curriculum at your leisure. If you decide for the minimal 2-3 hour weekly commitment, the certificate will take roughly 17 months to complete.

Cloudera – Data Platform Generalist Certification

The Data Platform Generalist test by Cloudera is excellent because it enables learners to take various roles within the data science industry. While the exam focuses on Cloudera’s data platform, the program certifies you as a general data science professional, meaning you can pursue a career in data engineering and analytics, development, administration, and similar fields.

The certification consists of a single 90-minute exam with 60 questions. Cloudera doesn’t state the minimal score needed to pass the exam because the point of the certification program is to do it the best you can rather than aiming for a specific score.

According to the Cloudera website, this certification costs $330. Upon completing the exam, you’ll get a certificate that lasts for two years.

IBM – Data Science Professional Certificate

As one of the industry leaders, IBM provides an exceptional course in data science. The course teaches the basics of data science, focusing on the work methodology via Python and SQL. The Data Science Professional Certificate program helps beginners in the field via hands-on work, with exercises in data set importing, analysis, cleaning, and visualization.

The online certificate course in data science consists of 10 parts. After the first three introductory courses, the following six focus on working in Python, while the final one deals with applied data science. This is a flexible, self-paced program suitable for beginners.

Enrolling in this IBM data science program is free via Coursera, provided you have a monthly subscription. The courses require about three hours of work per week. At that tempo, you should complete the program and receive your data science certification within five months.

Data Science Council of America – Senior Data Scientist

As the name implies, the Data Science Council of America (DASCA) counts among the leading authorities on data science in the U.S. and worldwide. The Senior Data Scientist program enjoys global recognition and takes place entirely online.

This program provides excellent resources that candidates can use to prepare for the exams. Plus, the resources are quality reading for the purposes of professional improvement. The learning material and the program itself are suitable for more experienced learners.

Upon enlisting, you’ll need to cover a one-time fee of $775. Once you receive the resources, you’ll have six months to prepare for the exam. The recommended study time is up to 10 hours weekly.

John Hopkins University – Data Science Specialization

When a reputable institution like the John Hopkins University offers a specialization in data science, there’s no reason to miss that opportunity. Hosted by Coursera, this Data Science Specialization course is built around practical applications of actual data.

The online program provides learners the chance to create a genuine data product. Along with learning, you’ll also be building a respectable portfolio that will come in handy as a demonstration of your newly acquired skills.

Like other Coursera programs, this specialization is also free with a subscription to the service. The program is flexible in terms of time commitment. If you devote an hour a day to it, you can complete the specialization in about 11 months.

Microsoft – Azure AI Fundamentals

Microsoft has proven to be not only a tech giant but an excellent knowledge hub. With Azure AI Fundamentals, this renowned company offers expertly crafted training in the basics of working with artificial intelligence. Through this certification program, learners can gain a thorough understanding of AI and become skilled in the latest technologies.

This online data science certificate course will be suitable even for complete beginners, although a basic level of programming skills would give you an easier start. The program comes in two variants: self-paced and led by a professional instructor.

The program costs only €99 and awards a permanent Microsoft certificate. You can also try out the course with a trial subscription, and there’s an available practice assessment test that will help you understand where you stand before enrolling.

MIT – MicroMasters Program in Statistics and Data Science

If you’re looking for an intensive program that will teach you advanced data science skills, MIT has just the thing. The MicroMasters in Statistics and Data Science is a result of a collaboration between the world-renowned MIT and edX, a trusted learning platform.

This program includes working on data sets from real-world examples, as well as understanding the leading machine learning models. Upon finishing, candidates will be eligible for different titles within the field of data science.

The program consists of five courses and may last up to 14 months with about 14 hours of weekly engagement. The edX platform lists the program price at $1,350.

Open Group – Certified Data Scientist

The Open Group consists of numerous global organizations, with some of the most distinct members being technology giants like IBM, Intel, Fujitsu, and Huawei. The Certified Data Scientist certification that the group provides is a credential recognizes around the globe.

The structure of this program is quite unique. It doesn’t include courses or exams. Instead, applicants need to demonstrate practical data science skills in written form. The point of this certification isn’t to educate, but rather to verify the candidate’s professional capabilities.

The time needed to get the certificate will vary depending on your proficiency level. The certificate is permanent, and Open Group discloses its price via contact.

Stanford University – Machine Learning Certification

Stanford University is home to some of the world’s finest lecturers. The institution provides a machine learning program in collaboration with Coursera and, as a practical, hands-on experience, it’s something eager learners shouldn’t miss.

The Machine Learning Certification is an ideal opportunity for beginners to grasp the intricacies of advanced AI and its applications. The program consists of three courses. By the end of the third course, the applicant should be able to build Python machine learning models from the ground up.

Following Coursera’s standard model, this program is free to enroll into, provided the user has a Coursera subscription. With up to nine hours of work weekly, the program shouldn’t last more than three months.

SAS – Certified AI and Machine Learning Professional

SAS is a certification program that operates globally. It offers a Certified AI and Machine Learning Professional program that’s built for people looking for top practical education in these areas. As the name says, this certification is aimed at future data science professionals.

The program includes five courses after which attendees get permanent certification. Upon registering, learners will receive a full year of access to the complete course material, as well as 70 hours of complimentary software use via cloud.

This program is self-paced, but you have to complete it within one year. The price for one year is €1,295.

Tips for Success in Data Science Certification Courses

Enrolling in a data science course is only a part of the process. To be successful, you’ll need to do your best and employ certain techniques:

  1. Manage your time effectively. Make sure to commit enough time to progress through the course and meet requested deadlines.
  2. Start building a network with your peers from day one. Collaborate with people who share your interest in data science so that you can build off of each other.
  3. Never assume you’ve learned everything there is to know. Data science is evolving constantly, and there’s always new skills to develop and additional knowledge to gain.
  4. Build a strong portfolio that will increase your chances of finding a job in the field. The best data science certification programs represent an ideal start.

Get Certified in One of the Top Professions Today

Getting a data science certificate online can open up a career path in a top-paid profession that continues to grow. With certification from one of the leading institutions in the field, you’ll be on the right track to success.

Our list contains programs and courses from renowned organizations like Harvard, IBM, MIT, and Microsoft. The quality of lecturers is unquestionable, and the programs offer the most up-to-date courses. Whichever certification you choose, you can rest assured you’ll be the best data science certification online.

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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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