In this three-day course, you will:
Data scientists, business analysts.
Some knowledge of R and/or Python is preferable but not required.
Hands-on lab environment will be provided by IBM.
Brandon MacKenzie is the Data Science on Hadoop leader on IBM’s Worldwide Technical Sales team for Information Management Software. He is an expert on statistical processing in Hadoop and HPC environments. Brandon earned his master’s degree from The University of Edinburgh.
John B. Rollins, Ph.D. is a data scientist in the IBM Analytics division of IBM. His background is in the fields of data mining, engineering, and econometrics in many industries. He holds seven patents, and has authored a best-selling engineering textbook and many technical papers. He holds doctoral degrees in economics and petroleum engineering from Texas A&M University.
Jacques Roy is a member of the IBM worldwide analytics platform technical team, specializing in big data streaming analytics. He has also worked in many technology areas including operating systems, databases, and application development. He is the author of multiple books, with the most recent being The Power of Now: Real-Time Analytics and IBM InfoSphere Streams. He is also a regular contributor to IBM Data magazine. Jacques has been a presenter at many conferences including IBM’s Information on Demand (IOD).
Chris Fregly is a senior developer advocate focused on AI and machine learning at Amazon Web Services (AWS). Chris shares knowledge with fellow developers and data scientists through his Advanced Kubeflow AI Meetup and regularly speaks at AI and ML conferences across the globe. Previously, Chris was a founder at PipelineAI, where he worked with many startups and enterprises to deploy machine learning pipelines using many open source and AWS products including Kubeflow, Amazon EKS, and Amazon SageMaker.
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