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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Il Sole 24 Ore: Integrating Artificial Intelligence into the Enterprise – Challenges and Opportunities for CEOs and Management
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 14, 2025 6 min read

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Expert Pierluigi Casale analyzes the adoption of AI by companies, the ethical and regulatory challenges and the differentiated approach between large companies and SMEs

By Gianni Rusconi

Easier said than done: to paraphrase the well-known proverb, and to place it in the increasingly large collection of critical issues and opportunities related to artificial intelligence, the task that CEOs and management have to adequately integrate this technology into the company is indeed difficult. Pierluigi Casale, professor at OPIT (Open Institute of Technology, an academic institution founded two years ago and specialized in the field of Computer Science) and technical consultant to the European Parliament for the implementation and regulation of AI, is among those who contributed to the definition of the AI ​​Act, providing advice on aspects of safety and civil liability. His task, in short, is to ensure that the adoption of artificial intelligence (primarily within the parliamentary committees operating in Brussels) is not only efficient, but also ethical and compliant with regulations. And, obviously, his is not an easy task.

The experience gained over the last 15 years in the field of machine learning and the role played in organizations such as Europol and in leading technology companies are the requirements that Casale brings to the table to balance the needs of EU bodies with the pressure exerted by American Big Tech and to preserve an independent approach to the regulation of artificial intelligence. A technology, it is worth remembering, that implies broad and diversified knowledge, ranging from the regulatory/application spectrum to geopolitical issues, from computational limitations (common to European companies and public institutions) to the challenges related to training large-format language models.

CEOs and AI

When we specifically asked how CEOs and C-suites are “digesting” AI in terms of ethics, safety and responsibility, Casale did not shy away, framing the topic based on his own professional career. “I have noticed two trends in particular: the first concerns companies that started using artificial intelligence before the AI ​​Act and that today have the need, as well as the obligation, to adapt to the new ethical framework to be compliant and avoid sanctions; the second concerns companies, like the Italian ones, that are only now approaching this topic, often in terms of experimental and incomplete projects (the expression used literally is “proof of concept”, ed.) and without these having produced value. In this case, the ethical and regulatory component is integrated into the adoption process.”

In general, according to Casale, there is still a lot to do even from a purely regulatory perspective, due to the fact that there is not a total coherence of vision among the different countries and there is not the same speed in implementing the indications. Spain, in this regard, is setting an example, having established (with a royal decree of 8 November 2023) a dedicated “sandbox”, i.e. a regulatory experimentation space for artificial intelligence through the creation of a controlled test environment in the development and pre-marketing phase of some artificial intelligence systems, in order to verify compliance with the requirements and obligations set out in the AI ​​Act and to guide companies towards a path of regulated adoption of the technology.

Read the full article below (in Italian):

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The Lucky Future: How AI Aims to Change Everything
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 10, 2025 7 min read

There is no question that the spread of artificial intelligence (AI) is having a profound impact on nearly every aspect of our lives.

But is an AI-powered future one to be feared, or does AI offer the promise of a “lucky future.”

That “lucky future” prediction comes from Zorina Alliata, principal AI Strategist at Amazon and AI faculty member at Georgetown University and the Open Institute of Technology (OPIT), in her recent webinar “The Lucky Future: How AI Aims to Change Everything” (February 18, 2025).

However, according to Alliata, such a future depends on how the technology develops and whether strategies can be implemented to mitigate the risks.

How AI Aims to Change Everything

For many people, AI is already changing the way they work. However, more broadly, AI has profoundly impacted how we consume information.

From the curation of a social media feed and the summary answer to a search query from Gemini at the top of your Google results page to the AI-powered chatbot that resolves your customer service issues, AI has quickly and quietly infiltrated nearly every aspect of our lives in the past few years.

While there have been significant concerns recently about the possibly negative impact of AI, Alliata’s “lucky future” prediction takes these fears into account. As she detailed in her webinar, a future with AI will have to take into consideration:

  • Where we are currently with AI and future trajectories
  • The impact AI is having on the job landscape
  • Sustainability concerns and ethical dilemmas
  • The fundamental risks associated with current AI technology

According to Alliata, by addressing these risks, we can craft a future in which AI helps individuals better align their needs with potential opportunities and limitations of the new technology.

Industry Applications of AI

While AI has been in development for decades, Alliata describes a period known as the “AI winter” during which educators like herself studied AI technology, but hadn’t arrived at a point of practical applications. Contributing to this period of uncertainty were concerns over how to make AI profitable as well.

That all changed about 10-15 years ago when machine learning (ML) improved significantly. This development led to a surge in the creation of business applications for AI. Beginning with automation and robotics for repetitive tasks, the technology progressed to data analysis – taking a deep dive into data and finding not only new information but new opportunities as well.

This further developed into generative AI capable of completing creative tasks. Generative AI now produces around one billion words per day, compared to the one trillion produced by humans.

We are now at the stage where AI can complete complex tasks involving multiple steps. In her webinar, Alliata gave the example of a team creating storyboards and user pathways for a new app they wanted to develop. Using photos and rough images, they were able to use AI to generate the code for the app, saving hundreds of hours of manpower.

The next step in AI evolution is Artificial General Intelligence (AGI), an extremely autonomous level of AI that can replicate or in some cases exceed human intelligence. While the benefits of such technology may readily be obvious to some, the industry itself is divided as to not only whether this form of AI is close at hand or simply unachievable with current tools and technology, but also whether it should be developed at all.

This unpredictability, according to Alliata, represents both the excitement and the concerns about AI.

The AI Revolution and the Job Market

According to Alliata, the job market is the next area where the AI revolution can profoundly impact our lives.

To date, the AI revolution has not resulted in widespread layoffs as initially feared. Instead of making employees redundant, many jobs have evolved to allow them to work alongside AI. In fact, AI has also created new jobs such as AI prompt writer.

However, the prediction is that as AI becomes more sophisticated, it will need less human support, resulting in a greater job churn. Alliata shared statistics from various studies predicting as many as 27% of all jobs being at high risk of becoming redundant from AI and 40% of working hours being impacted by language learning models (LLMs) like Chat GPT.

Furthermore, AI may impact some roles and industries more than others. For example, one study suggests that in high-income countries, 8.5% of jobs held by women were likely to be impacted by potential automation, compared to just 3.9% of jobs held by men.

Is AI Sustainable?

While Alliata shared the many ways in which AI can potentially save businesses time and money, she also highlighted that it is an expensive technology in terms of sustainability.

Conducting AI training and processing puts a heavy strain on central processing units (CPUs), requiring a great deal of energy. According to estimates, Chat GPT 3 alone uses as much electricity per day as 121 U.S. households in an entire year. Gartner predicts that by 2030, AI could consume 3.5% of the world’s electricity.

To reduce the energy requirements, Alliata highlighted potential paths forward in terms of hardware optimization, such as more energy-efficient chips, greater use of renewable energy sources, and algorithm optimization. For example, models that can be applied to a variety of uses based on prompt engineering and parameter-efficient tuning are more energy-efficient than training models from scratch.

Risks of Using Generative AI

While Alliata is clearly an advocate for the benefits of AI, she also highlighted the risks associated with using generative AI, particularly LLMs.

  • Uncertainty – While we rely on AI for answers, we aren’t always sure that the answers provided are accurate.
  • Hallucinations – Technology designed to answer questions can make up facts when it does not know the answer.
  • Copyright – The training of LLMs often uses copyrighted data for training without permission from the creator.
  • Bias – Biased data often trains LLMs, and that bias becomes part of the LLM’s programming and production.
  • Vulnerability – Users can bypass the original functionality of an LLM and use it for a different purpose.
  • Ethical Risks – AI applications pose significant ethical risks, including the creation of deepfakes, the erosion of human creativity, and the aforementioned risks of unemployment.

Mitigating these risks relies on pillars of responsibility for using AI, including value alignment of the application, accountability, transparency, and explainability.

The last one, according to Alliata, is vital on a human level. Imagine you work for a bank using AI to assess loan applications. If a loan is denied, the explanation you give to the customer can’t simply be “Because the AI said so.” There needs to be firm and explainable data behind the reasoning.

OPIT’s Masters in Responsible Artificial Intelligence explores the risks and responsibilities inherent in AI, as well as others.

A Lucky Future

Despite the potential risks, Alliata concludes that AI presents even more opportunities and solutions in the future.

Information overload and decision fatigue are major challenges today. Imagine you want to buy a new car. You have a dozen features you desire, alongside hundreds of options, as well as thousands of websites containing the relevant information. AI can help you cut through the noise and narrow the information down to what you need based on your specific requirements.

Alliata also shared how AI is changing healthcare, allowing patients to understand their health data, make informed choices, and find healthcare professionals who meet their needs.

It is this functionality that can lead to the “lucky future.” Personalized guidance based on an analysis of vast amounts of data means that each person is more likely to make the right decision with the right information at the right time.

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