How Does AI Work?

AI entered the mainstream in a big way when tools like ChatGPT by OpenAI and Google’s Gemini captured the world’s attention. Since then, it has reshaped how we think about work, decision-making, and what’s possible across industries, from healthcare to finance to logistics.

And while the technology has advanced rapidly in just a few years, we’re still in the early stages of what AI can do—and who’s equipped to use it.

That’s why CSU Global offers two flexible pathways designed for working adults at different stages in their tech journey:

• A master’s degree in artificial intelligence and machine learning
• An undergraduate certificate in Azure AI automation

“At CSU Global, we understand that students enter our AI program with a wide range of backgrounds, some come from non-technical fields, while others have advanced programming and data experience. It was important for us to design a single, unified program that is accessible to all learners but still rigorous enough to challenge those with more advanced technical skills,” said Matthew Brown, PhD., Lead Program Director. “The program scaffolds learning in a way that builds confidence and competence, ensuring students are progressively exposed to both foundational concepts and more complex, hands-on applications. Our goal is to prepare every student, regardless of starting point, to be job-ready in the evolving AI workforce.”

If you’re still getting familiar with the basics of artificial intelligence, here’s a quick overview — then we’ll show you how CSU Global can help you take the next step.

What Is Artificial Intelligence?

Artificial intelligence is a set of technologies that allow machines and computer programs to mimic human intelligence. AI systems learn from experience, identify patterns, and make decisions based on large volumes of data, often at a speed and scale far beyond what people can achieve alone.

AI isn’t a single tool. It’s a collection of algorithms, models, and systems used to solve complex problems, automate tasks, and support better decision-making.

How Does AI Learn?

At the core of most AI systems is machine learning, which allows programs to improve over time without being explicitly programmed. Here’s how it works:

• Massive Data Sets feed the system—everything from medical images to customer purchase histories.
• Intelligent Algorithms crunch that data repeatedly, learning which inputs lead to the best outcomes.
• Feedback Loops constantly refine the model’s accuracy, helping it “learn” from its mistakes and improve with each pass.

This process allows AI to develop insights, make predictions, and take actions based on data, all without needing step-by-step human instruction.

What is Generative AI?

Generative AI refers to a category of artificial intelligence that creates new content—text, images, code, audio, and more—based on what it has learned from existing data.

Tools like ChatGPT and Gemini are well-known examples. These platforms use large language models (LLMs) and deep learning to respond to prompts, summarize documents, generate creative writing, or even debug code. Generative AI tools are becoming essential for professionals in marketing, education, customer service, data analysis, and software development.

Here’s a closer look at what CSU Global’s two AI programs offer. Whichever path students choose, Brown said the focus is on graduating with the skills to make an impact.

“We want every CSU Global student to graduate from the program feeling confident in their ability to apply AI in real-world settings,” he said. “This means being able to analyze data, work with AI tools, understand ethical implications, and contribute to innovation within their organizations.”

The programs are designed to go beyond technical training, equipping students with the practical knowledge, adaptability, and critical thinking needed to succeed in a workforce that increasingly relies on AI-literate professionals.

What Disciplines Make Up the Field of AI?

There are many different components to an AI system, which you can think of as sub-fields of the overarching science of artificial intelligence.

Each of the following fields is commonly utilized by AI technology:

• Machine Learning – A specific application of AI that lets computer systems, programs, or applications learn automatically and develop better results based on experience, all without being programmed to do so. Machine Learning allows AI to find patterns in data, uncover insights, and improve the results of whatever task the system has been set out to achieve. Read more on machine learning vs AI to better understand how machine learning differs from and relates to AI.
• Deep Learning – A specific type of machine learning that allows AI to learn and improve by processing data. Deep Learning uses artificial neural networks which mimic biological neural networks in the human brain to process information, find connections between the data, and come up with inferences, or results based on positive and negative reinforcement.
• Neural Networks – A process that analyzes data sets over and over again to find associations and interpret meaning from undefined data. Neural Networks operate like networks of neurons in the human brain, allowing AI systems to take in large data sets, uncover patterns amongst the data, and answer questions about it.
• Cognitive Computing – Another important component of AI systems designed to imitate the interactions between humans and machines, allowing computer models to mimic the way that a human brain works when performing a complex task, like analyzing text, speech, or images.
• Natural Language Processing – A critical piece of the AI process since it allows computers to recognize, analyze, interpret, and truly understand human language, either written or spoken. Natural Language Processing is critical for any AI-driven system that interacts with humans in some way, either via text or spoken inputs.
• Computer Vision – One of the prolific uses of AI technologies is the ability to review and interpret the content of an image via pattern recognition and deep learning. Computer Vision lets AI systems identify components of visual data, like the captchas you’ll find all over the web which learn by asking humans to help them identify cars, crosswalks, bicycles, mountains, etc.

What Technology Does AI Require?

AI isn’t new, but its widespread application and utility have skyrocketed in recent years thanks to considerable improvements in technology.

In fact, the explosive growth of AI’s scale and value is closely related to recent technological improvements, including:

• Larger, More Accessible Data Sets – AI thrives on data, and has grown in importance alongside the rapid increase of data, along with better access to data. Without developments like “The Internet of Things”, which produces a huge amount of data from connected devices, AI would have far fewer potential applications.
• Graphical Processing Units – GPUs are one of the key enablers of AI’s rising value, as they are critical to providing AI systems with the power to perform millions of calculations needed for interactive processing. GPUs provide the computing power needed for AI to rapidly process and interpret big data.
• Intelligent Data Processing – New and more advanced algorithms allow AI systems to analyze data faster and at multiple levels simultaneously, helping those systems analyze data sets far faster so they can better and more quickly understand complex systems and predict rare events.
• Application Programming Interfaces – APIs allow AI functions to be added to traditional computer programs and software applications, essentially making those systems and programs smarter by enhancing their ability to identify and understand patterns in data.

How is AI Being Applied?

To fully get how AI works, it’s also important to understand where and how it’s actually being applied.

Fortunately, there are many examples of AI’s use in the modern economy, including:

• Retail – AI systems are being consulted to design more effective store layouts, handle stock management, and provide shopping suggestions, like via Amazon’s “You May Also Like” recommendations.
• Healthcare – AI technology has been trained to provide personalized medicine, including giving reminders about when patients need to take their medicine and suggestions for specific exercises they should perform to improve their recovery from injuries.
• Manufacturing – AI solutions help forecast load and demand for factories, improving their efficiency, and allow factory managers to make better decisions about ordering materials, completion timetables, and other logistics issues.
• Life Sciences – AI intelligence is actively applied to review complex data sets that are useful in testing new medicines, helping life science organizations get effective medicines to market faster.
• Finance – AI tools are being leveraged to detect and prevent fraudulent financial transactions, provide more accurate assessments than traditional credit scores can, and automate all sorts of data-related tasks that were handled manually.

Why Should You Consider Studying AI?

AI technologies are being developed and applied to virtually every industry, helping improve results, automate processes, and enhance organizational performance.

The AI industry itself is growing rapidly, with the International Data Corporation (IDC) reporting that the AI market, “including software, hardware, and services, is forecast to grow 16.4% year over year in 2021 to $327.5 billion.”

Top jobs in the field also tend to come with great salaries, with Glassdoor reporting that the average salary for AI engineers is $138K and $199K for AI development professionals.

If you’re interested in pushing the boundaries of computer technology and you want to launch a career in a field that’s growing, and pays well, then AI may be the perfect opportunity.

Why Should You Study AI With CSU Global?

Learn more details about our programs below.

Master’s Degree in Artificial Intelligence and Machine Learning

CSU Global’s online master’s degree in artificial intelligence and machine learning is designed for professionals interested in advanced concepts in programming, data science, and automation. The program emphasizes applied skills in software development, AI modeling, and machine learning implementation.

Students in this program:

• Apply software development techniques to AI and machine learning projects.
• Use AI and machine learning to address real-world problems.
• Build systems that simulate human behavior.
• Evaluate the performance and effectiveness of AI-driven solutions.

The program is intended for students with a strong foundation in math or programming who want to deepen their expertise.

Undergraduate Certificate in Azure AI Automation

CSU Global’s undergraduate certificate in Azure AI automation is an 18-credit program that introduces students to core concepts in artificial intelligence, machine learning, and cloud-based automation. The certificate is aligned with Microsoft’s Azure Data Engineering certifications and can be applied toward CSU Global’s Bachelor of Science in computer science.

Students in this program:

• Learn the fundamentals of machine learning.
• Work with core Azure services to build AI solutions.
• Use Azure Cognitive Services to automate tasks.
• Develop bots using Azure Bot Services.
• Explore advanced features in cloud-based AI platforms.

This certificate is designed for students looking to build job-ready skills in cloud and AI technologies. It is fully online and accessible to learners with a general familiarity with technology.

To learn more about CSU Global’s online AI programs, contact an enrollment counselor at enroll@csuglobal.edu or call 800-462-7845. You can apply here.