Harvard University · edX
Fundamentals of TinyML
4.567 ratingsFocusing on the basics of machine learning and embedded systems, such as smartphones, this course will introduce you to the “language” of TinyML.

In this intermediate-level specialization, you will build statistical and Machine Learning (ML)-based forecasts for business planning. You'll create time-series forecasts using Power BI, develop machine learning models with Azure AutoML, and evaluate forecast accuracy. You'll learn to communicate uncertainty and improve forecast reliability through iterative refinement.
This course is for financial professionals with 1–3 years of experience, including analysts, who have a foundational understanding of financial principles and standard data tools. By the end of this course, you will be able to apply Power BI forecasting tools for time-series predictions with confidence intervals, build machine learning models for revenue prediction using Azure AutoML, evaluate forecast accuracy to optimize model performance, and present forecast scenarios with appropriate uncertainty communication.
This course requires Power BI Desktop, which runs on Windows PCs or Macs with Parallels Desktop. A subscription to Azure ML is also required. Microsoft 365 online can be used as an alternative, though the desktop version is recommended for full feature access.
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Microsoft is in Tier 2: excellent universities and the companies that build the technology of our institution ranking (86/100).
Harvard University · edX
Focusing on the basics of machine learning and embedded systems, such as smartphones, this course will introduce you to the “language” of TinyML.
Harvard University · edX
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