Natural language processing, or NLP for short, has been making waves for years, but as of late, it has caught the attention of even non-tech enthusiasts. Why is that? Simply put, natural language processing bridges human language and computer understanding to make interactions feel more natural and less like talking to machines.

For tech professionals, NLP skills have grown from “nice-to-have” status a few years ago to some of the most significant skills of the decade. The field is growing quickly, and many are interested in taking on the challenge. Luckily, many resources online can get you there and are flexible, in-depth, and practical.

Understanding Natural Language Processing

Natural language processing is an element of artificial intelligence (AI) that deals with the interaction between computers and humans using natural language.

Traditionally, human-computer interactions have largely been done through predefined commands within terminals or graphical user interfaces that obscure the “commands” behind graphical interactions. These interactions work well and aren’t going away. However, instructing a computer by “speaking” to it has been within the realm of science fiction for decades but has also been a research goal of many computer scientists for a long while.

The goal of natural language processing is to read, decipher, understand, and make sense of human language in a valuable way. Recently, it has been integrated into everything from search engines figuring out what users are searching for to translating languages on the fly. It’s even a part of predictive text that finishes sentences, particularly on mobile phone keyboards. Taking a course in NLP gives you a new skill for the CV that opens doors to many employment positions across sectors.

Choosing the Right NLP Course Online

When searching for the right NLP course, consider what you need. Specifically, focus on these:

  • Curriculum
  • Instructors
  • Recognition
  • Experience

Does the curriculum cover the latest in NLP technology? The field evolves fast, sometimes with several breakthroughs or at least advancements a year. Course material and curriculum that’s several years behind might miss some of the new developments.

Are the instructors seasoned professionals? The more experience one has in the field, the better equipped they are to pass that knowledge down.

Is the NLP course recognized by industry leaders? It isn’t a matter of appealing to authority but rather knowing that the course is of high enough quality to be considered valuable and useful.

And let’s not forget about the hands-on experience. You can’t really learn NLP just by reading about it. It would be best to try your hands in real-life projects and workshops.

Most NLP courses will walk you through the basics of machine learning, algorithms that power NLP, and hands-on projects that solidify your knowledge.

OPIT offers a full NLP course as a part of the Master of Science (MSc) in Responsible Artificial Intelligence program. The course gives you a solid theoretical foundation and plenty of hands-on experience, presented by instructors who are experts in the field. The degree teaches you how to use NLP and use it ethically and responsibly.

A List of the Best NLP Online Courses

Here are some standout NLP online courses:

  • Coursera’s Natural Language Processing Specialization is for intermediate learners and spans over four months. It covers logistic regression, naive Bayes, word vectors, sentiment analysis, and more. The program is a comprehensive one that combines theory with practical assignments.
  • Stanford Online’s Natural Language Processing with Deep Learning focuses on the cutting-edge intersection of NLP and deep learning. It’s an in-depth exploration of NLP’s fundamental concepts and its role in emerging technologies. This course is perfect for those looking to get a solid foundation in NLP from one of the leading institutions in the world.
  • edX Natural Language Processing Courses & Programs: edX provides an intro to NLP that covers core techniques and computational linguistics. Topics include text processing, text mining, sentiment analysis, and topic modeling. It’s a great starting point for beginners and offers a broad overview of what NLP entails.
  • DeepLearning.AI’s Natural Language Processing in TensorFlow on Coursera was designed by one of the pioneers in AI education. It offers practical insights into implementing NLP techniques using TensorFlow. The course covers processing text, representing sentences as vectors, and building NLP models.
  • Udacity’s Natural Language Processing Nanodegree is project-focused with hands-on NLP learning. It covers foundational NLP concepts, including text processing, part-of-speech tagging, and sentiment analysis.

While these are the best natural language processing courses online, OPIT’s MSc in Responsible Artificial Intelligence, including NLP as part of its curriculum, is unique. This program teaches you NLP and embeds it within the broader context of artificial intelligence development, AI ethics, and responsible use. It’s excellent for those who want to go beyond the technical aspects and consider the societal impacts of their work in AI.

Benefits of Enrolling in an NLP Online Course

Attending an NLP course online might give you more than traditional on-site education. One of the biggest advantages is flexibility. You can learn at your own pace and on your schedule.

Online courses also open up networking opportunities with peers and mentors from around the globe. These are connections that on-site education would not have the scope to provide. Moreover, completing an NLP course can significantly boost your career prospects, potentially leading to job promotions and salary increases.

NLP Certification and Career Opportunities

With this certification, you’re proving your ability to understand and manipulate natural language data, making you invaluable in roles from data science and AI development to UX/UI design and content strategy.

Companies, from tech giants to startups, are on the lookout for professionals who can bridge the gap between human communication and machine understanding. The demand also translates into diverse job opportunities, competitive salaries, and the potential to work on groundbreaking projects in AI, machine learning, marketing, research, finance, and customer experience, among others.

Natural Machine Communication

NLP leads many of today’s technological advancements, making skills in this area more valuable than ever. Natural language processing courses that equip students with skills in natural language processing, AI, and related fields are growing in both offer and popularity. Completing one of these NLP courses sets you on a course for a financially promising career path within one of the most prestigious tech fields.

Get the right education and get ready for the future. Check out OPIT’s NLP course offerings within the MSc in Responsible Artificial Intelligence program or as a subject within our other computer science degrees.

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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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