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Applied Machine Learning

Applied Machine Learning Certificate

Discover the power of machine learning.

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has become pervasive and has resulted in self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Data scientists also think it is the best way to make progress towards human-level Artificial Intelligence (AI). There is power and value for individuals and firms capable of extracting knowledge, information, and insights from the sea of unstructured data.

Learn about the most effective machine learning techniques, and gain practice implementing and executing machine learning to work for you. These courses provide a broad introduction to machine learning, building on data mining, and statistical pattern recognition. Understand the theoretical underpinnings of learning and the practical know-how needed to quickly and powerfully apply these techniques to new problems.

Individuals who complete the Applied Machine Learning Certificate Program will have demonstrated, through practical “hands-on” experience, the ability to take plain unstructured data and create appealing, functioning, production-implemented machine learning solutions.

All tools and data utilized will be open source and freely available for use before, during, and after the course.

Take the 3-course certificate series or take just one course:

All courses will be available On Demand via Online Learning. Begin the certificate anytime; complete each course in 60 days.

The following order is recommended but not required:

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Title Session Dates Times Days Status
Developing Machine Learning Models Online 2021/22
  M Tu W Th F Sa Su   $ 595 Coming January 2022
Production Ready Machine Learning Online 2021/22
  M Tu W Th F Sa Su   $ 595 Coming April 2022
Structuring Data for Machine Learning Online 2020/21
  M Tu W Th F Sa Su   $ 695 Registration Available