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[title]Artificial intelligence applications are all the rage at the moment, and if you are looking to stay on the cutting edge of the tech world, you’ll want to learn how AI can help improve your workflow and general productivity. It is also a good way to become trained in an in-demand career field, since AI‑related hiring is rising 30% faster than overall recruitment, LinkedIn reports in 2025. While it may seem intimidating at first, learning the basics of AI can be rather accessible, even to professionals without prior experience, and more advanced AI techniques can be picked up with a bit of training and some dedication to the learning process. This article will help students who want to learn AI understand how challenging the training is likely to be and what different training options are available to them.
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What will you learn in an AI course?
One of the significant aspects of learning AI for professionals is that there are a few routes that you can take, and each of these paths will provide you with a different set of skills. When you enroll in an AI course, you’ll want to determine whether you are going to be learning how to work with AI (usually in a specific professional context) or how to build and program the AI that you and others will use (typically requiring deeper programming expertise). These are two very, very different skill sets, and they will determine whether you are looking at a relatively easy and accessible course that anyone can complete or a more immersive and difficult course with several prerequisite programming skills.
In a course focused on how to use AI and how it can be integrated into your regular workflow to become more productive, you are likely to spend the bulk of your time working on practical lessons focused on applying these tools to the kind of work that you are already doing. For example, if you are working as a graphic artist and you take a course like Noble Desktop’s AI for Graphic Artists program, you will learn how a tool like Adobe Firefly (which now comes as a default part of all of the major Creative Cloud applications) can be better integrated into your regular design work. The focus will be on using the tool, writing and refining prompts, checking the AI output for errors, and streamlining the process to save you time and energy on the rote or mundane aspects of the job.
In a course focused on developing and designing AI applications, you will focus on the internal workings of a machine learning application, and your training will focus on how to write code and train an algorithm to perform certain tasks based on the original data set. This involves a lot of training in both Python and theories of data science and analytics, particularly related to how one trains an AI to be effective and free from bias. Students who enroll in one of these courses are likely to need to learn far more advanced computer programming skills than they would in a more practical AI training course.
How hard are these AI skills to learn?
It should be stressed from the beginning that with enough time and effort, all of these skills can be learned by any student, and the discussion that follows is largely about how difficult classes are in relation to one another. Hard is also a relative concept, so what may be difficult for some students may come more easily to others. That said, there are some general facts about the difference between these two skill sets that will impact how hard they are to learn.
Learning to use AI as a practical tool in a specific professional context, like graphic design, finance, investment, or office management, can be learned with relative ease, particularly if you already have a background in the context in which you are going to be using the AI. In almost all of these contexts, you’ll be utilizing an already existing AI tool, like Microsoft CoPilot, OpenAI’s ChatGPT, or Adobe’s Firefly. This means that most of the work you do will be focused on learning best practices for working with these already established programs, which gives you a lot more room to learn via trial and error, and there are fewer fundamental skills you’ll need to understand in order to find success working with the applications.
By contrast, if you want to learn how to build and design your own AI tools, either for specialized tasks or as part of your dedicated career, you are going to need significantly more training, and that training will be significantly more technical in terms of the skills that it covers. To design an AI algorithm, you need to understand key principles of data science, data analytics, and machine learning, and you need an understanding of the Python programming language (and likely other programming languages related to working with large databases). This training is certainly going to be more intense than training for simply using already existing AI tools, but it is still very much an achievable goal for dedicated and determined students.
How to make AI training easier
One way to make learning AI-related skills easier is to enroll in a dedicated training program like those offered through Noble Desktop. These classes are ideal for students who need guided support and personalized feedback on their work as they learn the ins and outs of working with AI. These classes are taught by live instructors with years of relevant experience in their respective fields, meaning that you can be confident in the training that you are receiving and secure in the knowledge that your instructors understand the challenges that learning AI poses for new students. These courses are also beginner-friendly, so you don’t need a significant background in AI, and they tend to be career-focused courses, meaning that the lessons are going to be practical, real-world skills that students can start applying as soon as they complete the course.