Being highly technical, complex tech fields, those looking to enter the data and AI industry are recommended to pursue formal training in either area. You’re more likely to gain employer attention with recognised certifications under your belt, along with a strong portfolio of your previous experience.
Those in data science are often encouraged to specialise. Though your skills are applicable to any field, employers will typically seek out industry-specific experience, making it critical to hone your skills in your preferred sector. As mentioned, having at least a basic concept of machine learning and AI can help boost your employment value in the field.
Those in AI are required to build their knowledge on computer science, deep learning, neural networks, and machine learning to start exploring entry-level opportunities in the job or internship market. Of course, a fundamental understanding of big data and data analytics can help broaden your horizons.
On top of formal education, aspiring data and AI experts are also encouraged to expand their skills through personal practice. Plenty of online communities exist to help you learn from and collaborate with other like-minded professionals, these including Stack Overflow, Kaggle, and Dataquest for those in data science; and GitHub, Global AI Community, and r/machine learning (Reddit) for those into AI.