Machine Learning and Natural Language Processing define the current state of the art of Artificial Intelligence. These technologies, which are a form of data mining and data analysis, continuously learn from the provided information. They recognize hidden patterns that often provide dramatic competitive advantages at relatively low costs to the organization. These technologies are creating significant improvements in way we work, interact, and live producing efficiencies never imagined before. These methods are being applied in a diverse range of industries including: sales, marketing, advertising, health care, criminal justice, finance customer support and cool new industries like self-driving cars and highly efficient automated homes. Organizations today use these methods not only to improve their core business operations but also for developing new business models.
Deep Learning focuses on those Machine Learning tools that mimic human thought processes. Deep Learning can utilize a wide range of very large data sets (Big Data) in a vast array of formats (unstructured text, speech, images, audio and video). Machine Learning is dependent upon given features of the data to perform classification, detection, or prediction. Deep Learning is not dependent upon the representation of the data. It builds complex concepts from simpler models or data the same way the human brain processes large sets of inherently simpler stimuli to classify, recognize, analyze and synthesize. This layering of the network from simple to complex is Deep Learning. As these networks are inspired by the human brain, they are also called Artificial Neural Networks. Deep Learning algorithms and models are “trained” by the data (with guidance and monitoring from human insight) to solve a particular problem. Deep Learning Systems are designed to self-improve and get better as they process more data again mimicking how the human mind works.
Advances in Machine Learning and Deep Learning are helping to solve a very broad variety of problems including logistics, business process optimization, customer service, and health care.
By 2020, IT departments will be monitoring 50 times more data than they are today. This tidal wave of data has driven unprecedented demand for those with the skills required to manage and leverage these very large and diverse data sets into a competitive advantage for their organizations.
According to a recent McKinsey report, one of the key barriers in the adoption of Machine Learning is attracting and retaining the right talent in business people that combine data skills with industry and functional expertise. This program has been designed to help meet these expanding needs of business and industry for professionals who can effectively utilize both Machine and Deep Learning techniques to add value to any business.
Who Should Enroll
This program is intended for professionals in a variety industries and job functions who are looking to help their organization leverage the massive amounts of diverse data they collect and develop self-improving systems that improve their organizations ability to compete in the global market place. Specific job titles that would benefit from this program include: Marketing, Sales, Business Analysts, Data Engineers, Data Analysts, Computer Scientists, Database Administrators, Researchers, Statisticians, and those professionals looking to broaden their skills in this high-demand field while leveraging their unique domain expertise.
Occupational summary for computer and information research scientists in the United States.
Projected Growth (2017-2027)