In the world of analytics, few topics are hotter than machine learning. But the field is far from new. My first exposure to machine learning came in 1983 when I saw the movie WarGames with my family. The film was about a bored high school student, played by Matthew Broderick, who accidently hacks into a military supercomputer named Joshua. Thinking he had accessed a computer at a video game company, not one that controlled the US nuclear arsenal, Broderick innocently challenges Joshua to a game of thermonuclear war, nearly starting World War 3.
For a 13-year old boy, it was a pretty interesting film, and a little terrifying.
But the movie isn’t just memorable for me because it was my introduction to the Cold War. I was particularly fascinated by the movie’s computer co-star, Joshua. Joshua could take data – in this case, his opponent’s moves – learn from them and adapt his strategy in response, improving the odds of winning as the game progressed. This iterative process of “thinking and learning” is the concept behind machine learning.
A lot has changed since I was a newly minted teenager, besides my voice. Today, analytically mature organizations are using computers to learn from huge amounts of data. The process provides companies more accurate results or allows them to make better predictions of future outcomes. And organizations are using machine learning to accomplish some amazing things, everything from facial recognition to combat terrorists to recommender engines that suggest the next movie you should watch.
Given its prevalence, a good understanding of machine learning should be part of any good analytics professional’s skill set. Thankfully, SAS is here to help. Our new Predictive Analytics and Machine Learning training path can help you learn more about machine learning principles and the advanced analytics behind them. The curriculum is divided into three categories.
The Get Started category includes courses like Strategies and Concepts for Data Scientists and Business Analysts; SAS Visual Statistics: Interactive Model Building; and Getting Started With SAS In-Memory Statistics and introduces you to the concepts behind machine learning. Our Expand Your Skills grouping offers more advanced courses like Big Data, Data Mining and Machine Learning; Advanced Analytics in a Big Data World; and Predictive Modeling Using SAS In-Memory Statistics. The Dive Deeper series of courses is for the advanced learner. This grouping includes courses like Neural Network Modeling; Text Analytics Using SAS Text Miner; and Feature Engineering and Data Preparation for Analytics.
I encourage you to check out the full Predictive Analytics and Machine Learning training path curriculum for more details. Expanding your skills in these areas will really benefit your career. And I promise it won’t be scary at all!