Data science is big business and it’s only going to get bigger. Artificial intelligence may be the future, but that intelligence doesn’t mean much without big data, and data science is the philosopher’s stone for extracting actionable intelligence from otherwise incomprehensible blocks of information. Data scientists earn $110,000 on average, and that’s largely due to a high demand in the work force. Fortunately, starting your path to a career as a data scientist isn’t too hard. The following tips can serve as your goal posts on the way to success.
Get a Grip on Python
Python is one of the premier programming languages for tracking and managing data. It’s also fortunately one of the easier programming languages to learn. Its syntax largely mimics real language, and there’s a general sense of logic behind its functions. Of particular value is the Coursera class “Applied Data Science with Python” which can serve as a primer to Python and data science and help you get a feel as to whether data science is a tenable career track for you.
Understand Machine Learning, Deep Learning (or Both!)
There are two main methodologies in data science as it applies to artificial intelligence. Machine learning is essentially functional in design. It can constitute a variety of algorithms that are designed to achieve a singular purpose. This could mean parsing user browsing information to recommend them advertisements or sorting email messages into various folders based off their contents.
Machine learning AI progressively gets better with each iteration, but deep learning takes things to the next level. While the actual methodology behind deep learning is complex, it essentially models the same sort of thought processes as the human brain to facilitate more sophisticated thoughts, and it serves as the cutting edge for new artificial intelligence models.
Both machine learning and deep learning specializations are in high demand. The fast.ai resource is a great way to get a grip on machine learning, while a Deep Learning course by Andrew Ng can ground you in the fundamentals of deep learning.
The aforementioned resources can help you get an understanding of data science basics, but if you aren’t looking to engage in a traditional degree program, you’ll need to be voracious in your pursuit of knowledge. There are a ton of online classes and YouTube tutorials that can help you learn more about data science, and once you’ve learned the fundamentals, you should have an easier time tracking down the materials that are right for you.