Once thought the realm of science fiction, artificial intelligence is now a reality and is becoming more important every day. And as the field grows, so too do the job opportunities.
A career in artificial intelligence can be an exciting and fulfilling one, but it’s also a competitive field, and one that requires a lot of skill in some pretty technical areas.
Knowing what you need to know for a job in AI can be as tricky as the job itself. Luckily, we’re here to help. Let’s take a look at some of the most important tech skills you need for a career in AI.
What Does A Career In AI Look Like?
One of the biggest questions many people have is what a career in AI actually looks like. Many people may have a general idea, but the nuts and bolts of the job can be a mystery.
So what does a job in AI mean?
You may have heard some variation of the phrase “machine learning” before. That’s the gist of most AI jobs; helping computers better learn how to understand and react to the world around us.
In many cases, this involves things like image recognition, language interpretation, and other visual and auditory cues. Helping machines better understand these concepts is a critical part of AI work.
Those aren’t the only jobs available, of course. There are many jobs that focus more on the engineering side of AI. These jobs are less about the process, and more about the implementation.
These kinds of careers are heavily focused on taking AI that exists and finding ways to integrate it in the world around us. Still other jobs focus on the psychological and ethical side of AI. The opportunities are nearly limitless.
Common AI Skills
Before you narrow down which aspect of AI you want to work in, there’s a few skills you need to make sure you know. These skills will be important regardless of which specialty you choose to pursue.
Mathematics and Statistics
First and foremost, you need a good grasp of some pretty advanced mathematics. In particular, you need an expertise in algorithms. Algorithms serve as the bedrock for a large portion of AI programming.
Similarly, you need a good understanding of statistics and probabilities. A huge part of AI development is training a computer to make decisions based on probabilities.
In fact, statistics in particular is often a prerequisite for many jobs in AI. Artificial Intelligence requires an understanding of pretty advanced statistical models. Markov models and Gaussian Mixture models are just two examples of the kinds of advanced math at work in AI.
Aside from mathematics, the other most obvious requirement for AI careers is a solid grasp of programming languages. You need to have a high level of proficiency in a variety of programming languages, but especially Python, R, and C++.
- Python: useful for creating algorithms.
- R: designed for handling large amounts of data.
- C++: a popular and reliable language that is used all throughout software development.
Linux and UNIX
Nearly all work on AI is done on Linux machines. This means you’ll also need a strong grasp on UNIX tools. Luckily, Linux is already popular in many development fields, and resources for it are easy to find.
Before you decide what work you want to do in AI, you need to make sure you have a good grasp on these skills. You’ll use these often, regardless of the field of AI development you choose to enter.
AI Development Skills
Now that we’ve gotten the basic requirements out of the way, let’s take a look at some more specific skill sets that align to specific careers within the Artificial Intelligence industry. Let’s start with AI Development. This career path involves pioneering new advances in AI.
Expert Programming Skills
To create and build new Artificial Intelligence development, you can’t just “know” the programming languages outlined above – you need to be an expert. Python is the primary language used throughout AI and machine learning fields due to its effectiveness for algorithmic programming.
Advanced Statistics and Probability
Similarly, you need to make sure you know your math. Expert-level statistics and probability skills are essential. A huge portion of AI development is getting computers to properly understand and react to probabilities.
Linear algebra and calculus are also essential to thriving in the AI field. Matrix and vector math are commonplace in this field, and without a good understanding of them, you could find yourself lost before you get started.
Beyond that, you need to have a working knowledge of the technology of the industry. At this point, most people have heard of concepts like a neural network. You need to know what that means, how they’re built, and how they work. Neural networks are essentially AI in practice. If you can’t understand and work with them, you can’t thrive in AI development.
These are some pretty complex topics. Even the biggest experts in the field may need a refresher from time to time as the technology changes and advances.
AI Engineering Skills
If development jobs are what give life to AI, engineering jobs are what put the technology into practice. With an AI engineering job, it’ll be your task to take the technologies available and make usable programs out of them.
Naturally, this comes with its own set of skills. While there is some considerable overlap with other fields in AI, there are some unique things as well that you need to know.
As we mentioned earlier, one of the key functions of an Artificial Intelligence Engineer is to take AI models and turn them into usable programs. You need to be able to take the machine learning code and turn it into an API that other programmers can make use of.
To do so, you need a good grasp of what an API is. You also need to know how they should work, and how to effectively build one. Well-made APIs get AI in the hands of other software designers, so they can take advantage of it.
Data Analysis and Interpretation
A large part of your job will be data analysis. You need to be able to look at the real-world performance data of AI implementations. You then need to be able to use that data to make changes to the AI software.
As an engineer, the majority of your work involves these skills in some way. Optimizing the AI and finding new, more effective ways to implement it is the cornerstone of your job.
As such, you’ll need a strong grasp of data analysis. You’ll need to be able to spot and interpret trends, and make decisions based on that information.
Along these lines, you’ll need to be able to use data management apps. You’ll be using these more than other developers to keep track of and analyze trends in AI models.
The key skill here, as we’ve made clear, is data analysis and interpretation. That’s the main focus of your job as an engineer.
Non-Tech Skills (Soft Skills)
While the technical skills may be the most obvious, and most difficult, they aren’t the only skills you’ll need. The field of AI development requires an ability to work on a team and quickly analyze new information.
Teamwork Makes the Dream Work
Nearly all work in AI these days is a team effort. Regardless of your specific field, you’ll be working with other people, so interpersonal skills will be crucial. If you can’t effectively operate as part of a team environment, you’re going to struggle. The image of people cloistered away by themselves isn’t accurate.
Leadership and Management
As you continue to grow your career in Artificial Intelligence, you’ll likely have the opportunity to build your own team. As such, management skills and leadership skills will be very important to ensure that your team can function well.
Research is Key
You also need to have good documentation and research skills, and be able to analyze new information quickly. AI is an ever changing field, and new advancements are coming out all the time.
This includes knowing how to read and interpret AI research articles. Many of the newest developments in AI will first appear in research articles by your peers. Similarly, you should be able to write one yourself so that others can learn from your own discoveries and advancement.
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