Artificial Intelligence (AI) is one of the most innovative tech sectors of the day. Under its broad umbrella come other concepts such as machine learning and deep learning, which are two of the most prominent fields producing scientific breakthroughs. Before we begin to delve deeper into the subject matter and the opportunities that await, let’s familiarize ourselves with the fundamentals of AI.
What is AI?
AI refers to the application of computer science programming to enable machines and computers to mimic or perform certain tasks that otherwise would require human intelligence. In most cases, this is achieved by feeding data and algorithms to the computers. In today’s age, AI is used widely across the globe to power innovations such as virtual assistants, self-driving vehicles and even chatbots.
One of the most popular programming languages used in AI developments is Python. This is confirmed by a technical executive from IBM’s machine learning department, Jean Francois Puget. Python is a general-purpose language that can be used for just about anything, from developing a website to analyzing a huge amount of data. A huge number of programmers favor Python because its syntax is similar to the English language, making it easy to learn and understand.
Careers in AI
Here are some of the most prolific careers in the AI field:
Data Scientists are the individuals responsible for gathering, storing, analyzing and maintaining relevant data for an organization to derive actionable insights. These insights are presented to the decision-makers, helping the business assess if changes should be made to further optimize their operations. This is a highly lucrative role. According to Glassdoor, a Data Scientist in the US makes an average of $113,309 annually. Of course, the figure may differ according to the level of experience, location and employer.
Machine Learning Engineers
To put it simply, Machine Learning Engineers are professionals tasked with creating algorithms that can instruct computers or machines to mirror human behaviors. These algorithms are typically self-running, which means the designated tasks can be accomplished without human intervention. As the role requires a lot of technical expertise, these professionals are well-compensated, with Glassdoor citing an average income of $114,121 annually.
AI Software Engineers
Software Engineers generally develop software or programs by incorporating AI approaches or machine learning algorithms. While this may not sound too different from what Software Developers do, engineers can achieve bigger breakthroughs with different methodologies. According to Glassdoor, Software Engineers can bring home up to $134,000 per year.
Demand for AI Talent
Now that you’ve learned a little about what kind of careers and benefits you can gain from breaking into the AI sector, it is time to talk about the demand for AI talent and whether or not you should explore this opportunity.
It should be noted that AI Specialist is listed as the most promising career on LinkedIn’s Emerging Jobs Report 2020. With a recorded annual growth of 74 percent (when compared to the data from the past four years), LinkedIn said: “Artificial Intelligence and Machine Learning have both become synonymous with innovation, and our data shows that’s more than just buzz.”
Eaton Business School has also noted that AI skills—although of varying degrees—are required by all professions that are listed in the world’s 10 most in-demand jobs. The same report also acknowledged that there is a shortage of AI experts and recommended the field for those looking to launch themselves into a “super career”.
These reports not only illustrate the need for more AI talent in the field, but they also highlight how the field has grown and will continue to flourish. For job aspirants, this means room for career growth, lucrative perks and job security.
How to Learn AI
When it comes to preparing yourself with the right skillsets, you first have to decide which AI niche matches your personal and career goals the best. If you are thinking of making a career jump from a non-tech field, identify some transferable skills. After that, you can begin to acquire the technical knowledge needed to succeed in the AI field.
Generally, there are three ways to obtain an education: self-learning, traditional colleges or coding bootcamps—all with their own merits. While the first option is free, it may take a long time before you can truly master a skill like programming. Most times, an instructor is required to help you manoeuver the hurdles you face when coding.
The second option is the conventional route that most people opt for right after high school. However, it is also the most expensive choice. While most employers may favor job applicants with a bachelor’s or master’s degree, others place more emphasis on whether or not you can perform the necessary tasks. Bigger companies such as Google and Microsoft, for instance, are starting to forego conventional credentials when hiring.
The best way to go is probably the third option: coding bootcamps. They are short, intensive programs that focus on grooming students to be job-ready within months. Considering their duration, bootcamps cost a lot less than a university education. Most schools also offer flexible financing plans like income-sharing agreements and deferred payment plans to help students pay the tuition fees.