Artificial intelligence (AI) is a branch of computer science that involves programming machines to think like human brains. While simulating human actions might sound like the stuff of science fiction novels, it is actually a tool that enables us to rethink how we use, analyze, and integrate information to improve business decisions. AI has great potential when applied to finance, national security, health care, criminal justice, and transportation.
What is AI engineering?
Artificial intelligence engineers are individuals who use AI and machine learning techniques to develop applications and systems that can help organizations increase efficiency, cut costs, increase profits, and make better business decisions.
AI engineering focuses on developing the tools, systems, and processes that enable artificial intelligence to be applied in the real world. Any application where machines mimic human functions, such as solving problems and learning, can be considered artificial intelligence. Algorithms are “trained” by data, which helps them to learn and perform better.
What Does an AI Engineer Do?
An AI engineer builds AI models using machine learning algorithms and deep learning neural networks to draw business insights, which can be used to make business decisions that affect the entire organization. AI engineers also create weak or strong AIs, depending on what goals they want to achieve. AI engineers have a sound understanding of programming, software engineering, and data science. They use different tools and techniques so they can process data, as well as develop and maintain AI systems.
AI Engineers build different AI applications, such as contextual advertising based on sentiment analysis, visual identification or perception and language translation. The next section of How to become an AI Engineer focuses on the responsibilities of an AI engineer.
The 6 subsets of Artificial Intelligence
There are 6 main areas of focus when it comes to AI:
- Machine Learning (ML). Focuses on developing algorithms that enable computers to learn and make predictions or decisions based on data. This includes supervised learning (learning from labeled data), unsupervised learning (finding patterns in unlabeled data), and reinforcement learning (learning by taking actions and receiving rewards)
- Deep Learning. This is a subset of Machine Learning, but it’s big enough that it deserves its own mention. This involves developing artificial neural networks with multiple layers (hence the “deep”) that are inspired by the structure and function of the human brain.
- Computer Vision (understanding patterns in images/video). Focuses on getting computers to have an understanding of digital images and videos, which allows them to recognize faces, places, items, and more.
- Natural Language Processing a.k.a. NLP (or machines understanding language). Focuses on getting computers to understand, interpret, and even generate human language (in this case “natural” means human language, as opposed to computer language). This allows them to pick up on intent, language, and speech recognition, which is part of why ChatGPT seems so realistic
- Robotics. Everything from factory robots to perform tasks, to Roombas to map out and vacuum your home
- Decision Making. Using AI systems to mimic the decision-making ability of a human expert. This can have profound impacts on everything from medical treatments to weather forecasting.
How to become an AI Engineer in 5 steps
If we break it down into simple terms, there are really 5 major milestones that you need to cover, to become an AI Engineer:
- Learn the practical required skills to do the job (such as AI fundamentals + Python programming skills)
- Build a portfolio + GitHub/Hugging Face profile to prove you can do the work
- Gain experience by applying your new skills to hands-on projects (and then add these to your portfolio)
- Apply for jobs
- Prepare for the technical interview
AI Engineering is a highly promising and rewarding career choice. AI Engineers are in demand to drive innovative solutions and technological advancements and shape the future.