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.

Stop hiding workforce patterns in charts that mislead—learn to visualize turnover data that stakeholders can actually read, and use AI to articulate your findings clearly. In this hands-on course, you'll discover why chart type selection is not cosmetic, mastering the principle that a 3% difference visible in a bar chart can vanish in a pie chart. You'll learn to build clustered bar charts in Excel comparing quarterly turnover by gender, format them with clear labels and legends, and use ChatGPT or Claude to articulate the patterns in stakeholder-friendly language. Most importantly, you'll develop the ability to critically evaluate AI-generated descriptions and defend your visualization choices, explaining why clustered bars communicate comparison data more effectively than pie charts. Through realistic role plays and coach dialogues, you'll practice advising colleagues on chart selection, prompting AI for pattern articulation, and completing full visualization workflows. Designed for HR generalists, HR analysts, and people managers who present workforce metrics. Basic familiarity with Excel is helpful; no data visualization background is required.
Learn why the chart you choose fundamentally shapes what patterns your audience can see—and why pie charts often fail HR comparison tasks. Understand how clustered bar charts reveal trends across categories and time, and prepare to build your first turnover visualization by understanding Excel's ch…
Move from understanding to doing: build and format a complete clustered bar chart in Excel, use AI to articulate the patterns it reveals in stakeholder-friendly language, and learn to construct defensible arguments for your visualization choice. Complete the full workflow from raw data to AI-assist…
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Coursera is in Tier 4: commercial training companies and platform-made courses of our institution ranking (56/100). Made by the platform, often short guided projects.
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
Learn the concepts and techniques that make up the foundation of data science and machine learning.
Harvard University · edX
An introduction to the intellectual enterprises of computer science and the art of programming.
Harvard University · edX
Build a movie recommendation system and learn the science behind one of the most popular and successful data science techniques.
Massachusetts Institute of Technology · YouTube
Instructors: Esther Duflo and Sara Ellison View the complete course: https://ocw.mit.edu/courses/14-310x-data-analysis-for-social-scientists-spring-2023 This course introduces methods for harnessing data to answer questions of cultural, social, economic, and policy interest. We will start with esse…
Harvard University · edX
An introduction to programming using Python, a popular language for general-purpose programming, data science, web programming, and more.