You don’t need a computer science degree to be proficient in AI and gain a competitive edge in your … [+]
With employers viewing AI-ready employees as one of their most valuable assets in 2024, even being willing to boost salaries by as much as 47% for this in-demand skill—how exactly does one learn AI skills anyway?
Do you need to get a computer science degree to become AI-proficient for the workplace?
Thankfully not. Not everyone is ambitious to become a fully-fledged tech professional, or has the financial capacity or time to pursue a bachelor’s in computer science. But AI skills for work can be learned through other, cost-effective and less intensive methods.
1. Learn The Fundamentals Of AI
First, get to grips with the basics. Master artificial intelligence fundamentals by undertaking free courses such as Introduction to Artificial Intelligence by IBM, or Introduction to Generative AI by Google Cloud. These courses can help you feel more confident with understanding what this new technology is, and adding these certifications to your resume will already give you an edge against the job market competition.
2. Learn Programming Languages
You might want to take your technical skills and knowledge a step further and learn programming languages and how to code. Python is the most popular language for AI and machine learning, and R and SQL are both useful for data analysis, and managing and querying data. You can learn these through interactive learning platforms such Codecademy, Coursera, or freeCodeCamp.
3. Specialize Further
If you want to deep-dive further, why not take a machine learning course, such as the Deep Learning Specialization by Andrew Ng on Coursera? Many Coursera courses are free or are available for free once you complete the form that indicates you need financial aid, and this course is no exception.
4. Get Hands-On Practice
As you learn, gain hands-on experience, researching and discovering AI use cases and applications that best suit your role, department, and the industry you work in.
For example, Kaggle is a site where you can participate in competitions to practice real-world data science and machine learning problems. This is a fun and engaging way to learn and can help spice up your professional development experience.
You can also try your hand at building your own projects, just for fun, using datasets from sources such as Kaggle, UCI Machine Learning Repository, or open government data. Then, share your completed projects on GitHub and obtain feedback from other learners and those who are more experienced.
Sharing these projects with your employer proves to them that you are proactive and forward-thinking, and who knows, you might be the first person to come to mind when they look to hire for AI-focused roles in the near future.
5. Network With Others
Finally, what better way to brush up on your job-ready AI skills than to network with others who are doing the same? Connect with like-minded professionals through LinkedIn groups, online forums and Reddit subreddits such as r/MachineLearning, and even AI-focused Discord channels.
On Kaggle, you can keep your data science and AI skills fresh with games and competitions
Through gaining AI certifications, continuing to learn and specialize, and gaining hands-on experience while connecting with others learning AI skills including industry pros, you will soon become the go-to expert in your workplace for all things AI—and be on your way to a pay rise.