Artificial intelligence or AI has evolved from something you see at the movies to something you can use. It might not be immediately apparent to everyone. Still, AI is something you use every day; that’s why many people have looked into careers within Artificial intelligence.
For instance, the phone you use every day has AI to ensure ease of use, like using voice commands to play a song or open an application. That itself is AI on the move.
Also, when you snap photographs, you use AI to enhance and provide better picture quality. With that in mind, you might be interested in becoming an AI engineer.
Here’s a short guide that provides information and tips to help you become one and assess if diving into a career in AI Engineering is for you.
What is Artificial Intelligence?
Artificial Intelligence is a computer science branch specifically concerned with providing enough intelligence to execute specific tasks. You can do this by allowing machines to act and react based on a set of codes or programs.
However, the discipline itself is broader and more idealistic since it aims to provide actual intelligence to machines to learn and understand changes. As a result, you can create a fully independent machine and can learn on its own.
One of the most popular now is the self-driving cars that know how to drive on the roads.
Is an AI Engineer in Demand?
As mentioned, AI has already seeped into your daily lives. Thus, it shows how much AI is marketable.
In addition to phones and gadgets, the AI industry is widely used by car manufacturers and medical institutions. These institutions create AI to assess and assist people in the hospitals and on the road. And that’s only the tip of the iceberg. There are other more possibilities that AI can do for mankind. You can check this recommended reading to learn more about AI.
What Does an AI Engineer Do?
AI engineers don’t solely work alone to create an AI. Due to the complexity of AI programs, most AI engineers have teams that will work on specific projects based on the company’s industry. Team leaders will assign tasks or responsibilities to each engineer based on their background and specialty.
Mainly, these engineers work on the system and the algorithm that goes into the machines. However, these machines also work on actual models for testing.
Hence, engineers also build prototypes and samples where the algorithm is applied. This is where theory, codes, and models are combined, allowing a sample or proof of the concept. Inevitably, AI engineers will need to conduct this repeatedly to ensure a working program so technology can help every human being.
Furthermore, since the engineers are the experts, team leaders will be responsible for explaining essential milestones and the projects’ goals. These are explained to the investors, including other stakeholders. This allows the company to plan and manage the launch or failure of the project.
How To Become An Artificial Intelligence Engineer
First and foremost, you must understand that Artificial Intelligence has two main disciplines: Research and Development.
Thus, not everyone is designed to handle research and development at the same time. Although there are exceptional individuals that both have engineering degrees as well as PhDs for Artificial Intelligence. Hence, you must manage your expectations and understand your abilities.
If you prefer research, you must undergo a process of going through a bachelor’s, then a master’s, and finally completing a Doctorate for AI studies. This will provide the necessary credentials and skills to help advance your knowledge.
However, if you’re into the actual building of the machines and the application of the theories, the following are the necessary steps you must take to become an AI Engineer:
1. Gain Necessary Education
The first step is for you to finish an AI engineering course. Nowadays, many universities are providing AI engineering courses.
However, if none are available in your schools, look into computer science, robotics, physics, and other software development courses. With additional specialty classes, you can gain important information and knowledge.
This information will help artificial intelligence engineering since AI incorporates information from other disciplines to construct the program fully.
2. Enhance Technical Skills
Learning the principles of AI engineering isn’t enough. You should partner it with basic technical skills.
You can also practice as it’s the best way to develop your technical skills. Although finding practice for machine learning, coding, and neural networks will be difficult, try looking for freelance jobs to help develop your skills.
If you aren’t confident enough, you can look for workshops online. You can even find videos that include exercises and practices that will help you. Furthermore, don’t forget to fine-tune your mathematical skills as they’ll come in handy for specific projects.
3. Master Programming Languages
Since programming will be the main driving force in AI projects, it’ll be beneficial to learn programming languages.
That’s why you should take online courses for these languages, such as Python and C ++. If possible, try to study as much language as possible as different projects might use different languages.
Also, supplement it with other classes to better understand the incorporation of hardware into the software. This will enable you to understand the flow and direction of the projects to becoming an AI engineer.
4. Incorporate Necessary Business Skills
Besides being technical know-how, you should also take other classes and courses necessary to build a career in AI engineering. Here are a few more basic skills you need to have and hone:
- Innovative Reasoning: Since the discipline is relatively new and future-based, it’s essential to have an open mind. Thus, allowing you to see future problems, in addition to the possibilities that it’ll bring.
- Problem Solving Skills: With any project, there’ll always be problems. When developing AI, one single problem can influence the whole project. Thus, it’ll be essential to beef up your problem-solving skills, especially for AI projects that involve state-of-the-art technology.
- Ability to Work in A Team: As previously mentioned, these projects will involve team management and teamwork. If you’re unable to work with your team, the project can result in a standstill since every division must work with each other to build the full AI.
5. Seek A Position
If you’ve followed this guide diligently, you can now start your career in AI engineering. The vital thing to note is to look for any job that will start you off in the industry.
You may start looking into assistant jobs for different markets such as education, medicine, or even marketing. However, make sure to choose a position that best fits your experience, education, and skills.
Conclusion
Becoming an AI Engineer is all about having the knowledge and skills for the job. This is why most of the guide pushes you to learn and enhance your skills since this will be the basis of where you start and how well you can succeed in the industry.
Furthermore, don’t get discouraged when looking for a job. Although finding your first job will be difficult, you’ll eventually land a good starting position.
Meanwhile, expand your resume with jobs that will show your skills in programming and development. Lastly, in an industry that’s steadily growing and evolving as we speak, don’t forget to enhance your knowledge constantly. This will give you the edge over other AI engineers.
