MLOps2 (Azure): Data Pipeline Automation & Optimization using Microsoft Azure Machine Learning

مقدمة من

شعار المنصة
متاح الآن إلى 2024-12-31
24.00 ساعة تعليمية
متوسط
اللغة :
الإنجليزية
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نبذة عن المقرر

Most data science projects fail. There are various reasons why, but one of the primary reasons is the challenge of deployment. One piece to the deployment puzzle is understanding how to automate your pipeline’s functions and continuously optimize its performance, which is why we developed this course, MLOps2 (Azure): Data Pipeline Automation & Optimization using Microsoft Azure Machine Learning. In this course you will learn how to set up automated monitoring of your data pipeline for prediction. Data drift, model drift and feedback loops can impair model performance and model stability, and you will learn how to monitor for those phenomena. You will also learn about setting triggers and alarms, so that operators can deal with problems with model instability. You will also cover ethical issues in machine learning and the risks they pose, and learn about the "Responsible Data Science" framework.

المدربين

Peter Bruce
Peter Bruce

Peter founded the Institute for Statistics Education at Statistics.com which was acquired by Elder Research, Inc. in 2019, The Institute specializes in introductory and graduate level online education in statistics, optimization, risk modeling, predictive modeling, data mining, and other subjects in quantitative analytics.

Evan Wimpey
Evan Wimpey

Evan brought his military experience to Elder Research to deliver client solutions as a Data Scientist. He now serves as the Director of Analytics Strategy, helping to marry the exciting things that analytics can do with the myriad of challenges that people are facing. Evan almost always has a smile on his face, and that smile is the widest when he is helping organizations use data in new ways to solve unique problems.

Vic Diloreto
Vic Diloreto

Vic leads the software engineering group at Elder Research. In this role, Vic is chartered with the continuing support of our data science service to clients where software is needed in data preparations and/or visualizations. Vic is also leading the efforts to convert select portions of Elder Research’s intellectual property library into standalone products.

Laura Lancheros
Laura Lancheros

Laura is passionate about creating collaborative analytics solutions and challenging traditional paradigms to find innovative ways to meet client needs. Prior to joining Elder Research, Laura worked for more than a decade at an independent research organization as a researcher, project manager, and quality assurance professional to help government and nonprofit clients make better decisions through data and analysis.

Greg Carmean
Greg Carmean

Greg is a data scientist and enjoys helping clients solve business problems and improve their processes. Previously, he was a Data Analyst for the US Navy where he led software development efforts for his group. He leveraged data to solve scientific and operational problems and co-led the development and deployment of an analytics product which more than doubled fleet demand for his group’s services.

Bryce Pilcher
Bryce Pilcher

Bryce brings a background in network simulation and software reliability to client tool design. Bryce has leveraged graphs and Java to provide a new interfaces for clients to look at and interact with their data. His love of learning has led him to use Python for gathering useful information from the web and Scala to develop functional and reliable software solutions.

Kuber Deokar
Kuber Deokar

Kuber is responsible for the coordination of online courses and ensures seamless interactions between the management teams, course creators, course instructors, teaching assistants, and students. Kuber also handles continuous course improvement projects in his capacity as Data Science Lead at UpThink Edutech Services. He has a special interest in Machine Learning, Predictive Analytics, Statistical Modeling, SQL, R, and app development.

Janet Dobbins
Janet Dobbins

Janet works with colleges and universities to create innovative curriculum; and industry teams to help them gain necessary data science and technical skills.

She is on the Board and past President of Data Community DC, a non-profit 501(c)(3) corporation committed to promoting data science by fostering education, opportunity, and professional development through high-quality community-driven events.