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Professional Certificate in
Machine Learning Operations with Microsoft Azure (MLOps with Azure)
Statistics.comX

What you will learn

  • How to create a pipeline using Azure to ingest data to train a predictive model and feed it as it operates.
  • How to have the model score the data on an ongoing automated basis.
  • How to design the pipeline to output a decision or action variable.
  • How to continuously monitor several points of operation, including the incoming data (for data drift) and the decision outputs (for anomalies).
  • How to forge an appropriate AI engineering role in your organization.

Machine Learning Operations (MLOps) lies at the core of the AI Engineering function. In Statistics.com’s MLOps with Azure program you will learn to combine data engineering and data science skills to deploy machine learning models.

Most of the work in deploying AI models does not lie in developing models. Rather, it lies in developing, monitoring and maintaining an automated, self-monitoring data pipeline through a model and into actions. The common practice of tossing a project back and forth between pure data scientists and pure data engineers leads to delay and errors. This has created a need for AI engineers who have knowledge of each function. Mastering machine learning deployment skills on the Microsoft Azure platform is a sure path to career success.

In this course, you will learn how to work with data scientists to deploy machine learning models that can learn from data, and generate predictions, recommendations or decisions. This process usually is automated and that is where MLOps and AI engineering skills are needed.

You will focus on developing the skills needed to create a Microsoft Azure pipeline that:

  • Ingests data to train a predictive model
  • Feeds the model as it operates
  • Scores the data on an ongoing basis
  • Outputs an action
  • Integrates into business applications

Additionally, you will learn to develop the pipeline so that it will continuously monitor several points of operation, including the incoming data (for data drift) and the decision outputs (for anomalies). Statistics.com is the training platform of Elder Research (elderresearch.com), an internationally recognized data analytics consulting firm that, since 1995, has consulted for hundreds of leading businesses in data strategy, data science, and data engineering. Elder Research leverages the wisdom gained by solving a wide variety of real-world problems to infuse their education programs on the Statistics.com platform with the most cutting-edge training that can be applied day one.

Expert instruction
3 skill-building courses
Self-paced
Progress at your own speed
3 months
5 - 7 hours per week
$447
USD
For the full program experience

Courses in this program

  1. Statistics.comX's Machine Learning Operations with Microsoft Azure (MLOps with Azure) Professional Certificate

  2. 5–7 hours per week, for 4 weeks

    What is Predictive Analytics? These methods lie behind the most transformative technologies of the last decade, that go under the more general name Artificial Intelligence or AI. In this course, the focus is on the skills that will allow you to fit a model to data, and measure how well it performs. We will be doing enough data science so that you get hands-on familiarity with understanding a dataset, fitting a model to it, and generating predictions.

  3. 5–7 hours per week, for 4 weeks

    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 data engineers can effectively work with data scientists to monitor and iterate on model performance, which is why we developed this course: Machine Learning Ops (MLOps1) - Deploying AI & ML Models in Production using Microsoft Azure Machine Learning (AML)

  4. 5–7 hours per week, for 4 weeks

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

    • AI Engineering, with MLOps at its heart, is an emergent discipline focused on developing tools, systems, and processes to enable the application of artificial intelligence in real-world contexts.
    • Employment in the field of AI and related information technology generally is expected to grow faster than the average for all occupations (according to the BLS).
    • In AI Engineering specifically, according to Indeed, job openings grew 344% between 2015 to 2018 and have an average base salary of $146,085.

Meet your instructors
from Statistics.com (Statistics.comX)

Evan Wimpey
Director of Analytics Strategy
Elder Research
Vic Diloreto
Chief Technology Officer
Elder Research
Laura Lancheros
Analytics Engagement Manager
Elder Research
Greg Carmean
Data Scientist
Elder Research
Kuber Deokar
Data Science Lead
UpThink Experts; Faculty and Instructional Operations Supervisor at The Institute for Statistics Education at Statistics.com/ An Elder Research Company
Janet Dobbins
Director, Training Business Development
Elder Research
John Elder, IV
Chairman of the Board and Founder
Elder Research
Shree Taylor
Vice President, Government Analytics & Innovation
Elder Research
Bryce Pilcher
Senior Data Engineer
Elder Research
Allison Marrs
Software and Data Engineer
Elder Research
Ramzi Ziade
Analytics Engagement Manager
Elder Research
LeAnna Kent
Senior Data Scientist
Elder Research
Henry Mead
Data Scientist
Elder Research, Inc
Peter Bruce
Chief Learning Officer
Elder Research and Founder of The Institute for Statistics Education at Statistics.com
Veronica Carlan
Data Scientist
Elder Research
Jericho McLeod
Data Scientist
Elder Research

Experts from Statistics.comX committed to teaching online learning

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$447
USD
3 courses in 3 months
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