Elder Research and Statistics.com Launch Machine Learning Operations Certificate Program on edX

Elder Research, an internationally recognized data analytics solution consultant with over 25 years of expertise in data strategy, data science, data engineering, and training, and its training platform Statistics.com, announced the launch of a partnership with edX. This partnership creates a unique series of practical training content leveraging Elder Research’s industry expertise and Statistics.com’s excellence in online training. With edX, Elder Research has created the first series of Machine Learning Operations (MLOps) courses which include hand-on learning labs. This partnership is in response to increasing demand for high quality training on AI Engineering, and Machine Learning technology and operations.

“We are delighted to welcome Statistics.com to the edX partner community with its cutting-edge machine learning Professional Certificate programs,” said Anant Agarwal, edX Founder and 2U Chief Open Education Officer. “Machine learning is one of the most in-demand technology skills and I’m excited to bring this relevant learning content to our global community of learners.”

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Learners will have the opportunity to gain certificates of completion through a program consisting of the following series of courses:

• Predictive Analytics: Basic Modeling Techniques
• MLOps-1 (MLOps: Deploying AI & ML Models in Production)
• MLOps-2 (MLOps: Data Pipeline Automation & Optimization)

Courses support the use of Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure Machine Learning (AML).

According to Peter Bruce, Chief Learning Officer of Elder Research and Founder of Statistics.com, “most machine learning projects fail to create value. In most cases, the machine learning model works, but deployment is difficult and often leads to maintenance headaches, and is abandoned. In this Program you’ll learn how to set up data pipelines, embed models, implement monitoring mechanisms, configure the action that results from monitoring, and much more that will help your machine learning projects succeed.”

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