Are you fascinated by the world of artificial intelligence? Do you often find yourself asking: "how can I become an AI engineer?" If so, then you're in the right place!
In this comprehensive guide, we're going to unveil the process of becoming an AI engineer, the skills required, and the opportunities within this burgeoning field.
Plus, we'll delve into the importance of continuous learning and professional development.
Whether you're an aspiring AI engineer or considering a mid-career transition into the world of AI, we've got you covered. Spend some time with us, and by the end of this article, you'll have a solid roadmap for how to become an AI engineer.
What is AI engineering?
Simply stated, artificial intelligence Engineering is a multidisciplinary blend of several branches of computer science, and it's the driving force behind many of the innovative advancements we see today. It incorporates elements of data science, artificial intelligence, statistical analysis and complex networks to fabricate highly intelligent machine learning algorithms and models.
The primary goal of AI engineering is to design intricate software systems that mimic the capabilities of the human brain. These cover a wide spectrum - from understanding and processing natural language and recognizing complex structures in a visual field, to making calculated decisions and even learning from past experiences.
The heart and soul of artificial intelligence engineering lie in creating artificial intelligence models, often referred to as AI models, that can generate valuable insights in various sectors, ranging from healthcare to finance to business operations.
At its core, AI engineering is reliant on the application of various types of machine learning algorithms, programming languages, and data structures to build, test, and deploy AI models, which are then capable of performing tasks requiring human-like intelligence.
AI engineering career prospects and salaries
AI engineering jobs are on the rise across numerous industries. According to the U.S. Bureau of Labor Statistics, the number of AI jobs is expected to increase by 23% over the next decade - almost 5 times as much as the overall industry growth rate. In 2020, Forbes analysed data from LinkedIn and declared AI specialist as the top emerging job on the market.
The average salary of an AI engineer in the United States currently sits at around $120,000 per year (according to Glassdoor). Adobe has recently posted an AI engineer position offering up to $250,000 per year. Clearly, AI engineering salaries are some of the highest in the world.
Given the potential of AI and deep learning to spot trends and make predictions, well-trained AI engineers are in high demand, and prospects seem set to grow even further.
What does an AI engineer do?
Have you ever wondered about the daily responsibilities of artificial intelligence engineers? You're not alone! With careers in artificial intelligence engineering on the rise, a lot of people share your curiosity.
AI engineers are primarily tasked with designing and implementing AI models by harnessing machine learning and data science. They play a crucial role, working hand-in-hand with a data science team to bring theoretical data science concepts to life with practical applications.
Their tasks are varied and encompass several areas. A few notable responsibilities of artificial intelligence engineers include:
- Building artificial intelligence systems and AI models that can process and learn from large volumes of data to uncover valuable insights
- Performing statistical analysis and complex network programming
- Deploying the applications they build to production environments
- Implementing proper data sharing techniques that promote data accessibility
- Keeping artificial intelligence systems up-to-date by conducting maintenance and continuously improving these systems
What sets AI engineers apart from traditional software engineers is their ability to work with highly complex data structures, neural networks, deep learning and other sophisticated machine learning models. It's all about leveraging vast computational power to solve complex challenges.
AI engineering: scope
With the technology landscape constantly evolving, the scope of AI engineering is steadily increasing as well.
AI is often likened to the human brain of computer systems, having the uncanny ability to replicate human intelligence, understand and learn from complex data, automate processes, and solve problems efficiently.
From offering valuable business insights that drive strategic decision-making to streamlining business process management, AI-based applications are seeing widespread adoption in various realms.
We've even highlighted some of the major benefits AI has brought to higher education, like the wide range of time management tools students can now use.
