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Project Planning and Machine Learning

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Free Online Course: Project Planning and Machine Learning provided by Coursera is a comprehensive online course, which lasts for 4 weeks long, 17 hours worth of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from Coursera. Project Planning and Machine Learning is taught by David Sluiter.

University of Colorado Boulder via Coursera
4 weeks long, 17 hours worth of material
Upcoming
Overview

  • This course can also be taken for academic credit as ECEA 5386, part of CU Boulder’s Master of Science in Electrical Engineering degree.

    This is part 2 of the specialization. In this course students will learn :
    * How to staff, plan and execute a project
    * How to build a bill of materials for a product
    * How to calibrate sensors and validate sensor measurements
    * How hard drives and solid state drives operate
    * How basic file systems operate, and types of file systems used to store big data
    * How machine learning algorithms work - a basic introduction
    * Why we want to study big data and how to prepare data for machine learning algorithms

Syllabus

    • Project Planning and Staffing
      • In this module I share with you my experience in product planning, staffing and execution. You will perform a product tear down, write a paper about your tear down and build a bill of materials (BOM) for that product.
    • Sensors and File Systems
      • In this module you will learn about sensors, and in this case, a temperature sensor. You will learn how to calibrate and then validate that a temperature sensor is producing accurate results. We will study how data is stored on hard drives and solid state drives. We will take a brief look at file systems used to store large data sets.
    • Machine Learning
      • In this module we look at machine learning (ML), what it is and how it works. We take a look at a couple supervised learning algorithms and 1 unsupervised learning algorithm. No coding is required of you. Instead I provide working source code to you so you can play around with these algorithms. I wrap up by providing some examples of how ML can be used in the IIoT space.
    • Big Data Analytics
      • In this module you will learn about big data and why we want to study it. You will learn about issues that can arise with a data set and the importance of properly preparing data prior to a ML exercise.

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