Project Planning and Machine Learning

Project Planning and Machine Learning

This course is part of Developing Industrial Internet of Things Specialization

Instructor: David Sluiter

Access provided by Abu Dhabi National Oil Company

13,324 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

132 reviews

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

132 reviews

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Create a plan to staff and execute a project to a schedule.
Create and calibrate sensor systems. Describe how hard drives and solid state drives operate. Describe how file systems for big data work.
Describe the basic operation of today's machine learning algorithms.
Describe the basics of big data analytics.

Skills you'll gain

Details to know

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Assessments

4 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the Developing Industrial Internet of Things Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in this course

Products don't design and build themselves. In this course, students learn how to staff, plan and execute a project to build a product. We explore sensors, which produce tremendous volumes of data, and then storage devices and file systems for storing big data. Finally, we study machine learning and big data analytics.

This course can be taken for academic credit as part of CU Boulder’s Master of Science in Electrical Engineering (MS-EE) degree offered on the Coursera platform. The degree offers targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Electrical Engineering: https://www.coursera.org/degrees/msee-boulder

In this module I share with you my experience in product planning, staffing and execution. You will learn about the importance of first defining requirements, second performing the design work first, and then lastly writing the code.

What's included

8 videos3 readings1 assignment1 discussion prompt

8 videos Total 128 minutes

1 - Course Overview 3 minutes
1 - Introduction to Project Planning 16 minutes
2 - Requirements and Scope 18 minutes
3 - Roles and Responsibilities, Design Process Part 1 19 minutes
4 - Design Process Part 2 and Part 3 20 minutes
5 - Validation and the Agile Process 24 minutes
6 - Documentation 18 minutes
7 - Product Tear-down and Bill of Materials 10 minutes

3 readings Total 17 minutes

Non-Credit Students: Welcome and Where to Find Help 10 minutes
A Note from the Instructor 5 minutes
Additional Course Resources 2 minutes

1 assignment Total 10 minutes

Project Planning and Staffing Quiz 10 minutes

1 discussion prompt Total 10 minutes

Introduction Discussion Forum 10 minutes

In this module you will learn about sensors, and specifically a temperature sensor. You will learn how to calibrate a temperature sensor system, which helps you measure and improve the accuracy of that system. You will learn how data is stored on hard drives and solid state drives. You will learn about 3 file systems that are used to store large data sets, which are often referred to as "Big Data".

What's included

7 videos1 assignment

In this module we look at machine learning (ML), what it is and how it works. You will learn about several 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 Industrial IoT space.

What's included

10 videos10 readings1 assignment

10 videos Total 128 minutes

1 - Machine Learning Part 1 14 minutes
2 - Machine Learning Part 2 13 minutes
3 - Machine Learning Part 3 26 minutes
4 - Machine Learning Part 4 10 minutes
5 - Machine Learning Part 5 9 minutes
6 - Machine Learning Part 6 8 minutes
7 - Machine Learning Part 7 9 minutes
8 - Machine Learning Part 8 14 minutes
9 - Machine Learning Part 9 10 minutes
10 - Machine Learning Part 10 15 minutes

10 readings Total 83 minutes

READ ME 1 minute
Machine Learning Code Examples .zip file 2 minutes
Required Reading: MLM - Test and Validation Datasets 10 minutes
Optional Reading: The Human Promise of the AI Revolution 10 minutes
Optional Reading: Lenovo - Debunking Misconceptions About AI 10 minutes
Optional Reading: Wired - Neuroscience Key to True AI 10 minutes
Optional Reading: IEEE Spectrum - 7 Revealings Ways AIs Fail 10 minutes
Optional Reading: IEEE Spectrum - AI Risks 10 minutes
Optional Reading: IEEE Spectrum - Don't Trust Deep Learning 10 minutes
Optional Reading: IEEE Spectrum - Why Worry About Superintelligent AI 10 minutes

1 assignment Total 24 minutes

Machine Learning Quiz 24 minutes

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 Machine Learning exercise.

What's included

9 videos4 readings1 assignment

9 videos Total 104 minutes

1 - Introduction Part 1 12 minutes
2 - Introduction Part 2 17 minutes
1 - Getting Started 5 minutes
1 - Issues with Data Part 1 13 minutes
2 - Issues with Data Part 2 8 minutes
1 - Learning from Big Data Part 1 13 minutes
2 - Learning from Big Data Part 2 16 minutes
1 - Personal Example from the Instructor 14 minutes
1 - Summary 5 minutes

4 readings Total 134 minutes

Code for the NFL Prediction Example 2 minutes
Please Watch: The 7 Principles of the IoT (and two other 7's) 16 minutes
Optional Reading: Matillion - Data Lakes 74 minutes
Optional Reading: Matillion - Data Analytics Platform 42 minutes

1 assignment Total 24 minutes

Big Data Analytics Quiz 24 minutes

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Build toward a degree

This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹