University of Colorado Boulder - Project Planning and Machine Learning 

Introduction

Segment 1 - Learning Outcomes, Introduction to a Design Process

Segment 2 - Requirements, Scope, Schedule, Resources, Heap Chart

Segment 3 - Roles and Responsibilities

Segment 4 - Process: Architecture Definition, Design Planning

Segment 5 - Process: Architecture Definition, Design Planning 2

Segment 6 - Process: Develop

Segment 7 - Process: Verification

Segment 8 - Process: Manufacture

Segment 9 - Process: Deploy

Segment 10 - Process: Validation

Segment 11 - Temperature

Access to Course Resources

A Note from the Instructor

Module 1 Quiz

Introduction

Segment 1 - Learning Outcomes, Introduction to Thermistors

Segment 2 - Terminology: Resolution, Precision, Accuracy, Tolerance

Segment 3 - Basic Sensor Circuit

Segment 4 - Accuracy Example

Segment 5 - Calculating Rtherm

Segment 6 - Validating Calibration

Segment 7 - Filtering Techniques

Segment 8 - Block, Object and Key-Value Storage Devices

Segment 9 - Filesystem Basics

Segment 10 - A File on a Hard Drive

Segment 11 - A File on a Solid State Drive

Segment 12 - File System: NFS

Segment 13 - How Big is "Big"?

Segment 14 - Traditional File System Bottlenecks

Segment 15 - Parallel Distributed File Systems: Hadoop, Lustre

Module 2 Quiz

Introduction

Segment 1 - Learning Outcomes

Segment 2 - AI Backgrounder

Segment 3 - Machine Learning, What is it?

Segment 4 - Machine Learning Schools of Thought

Segment 5 - Get the Tools

Segment 6 - Categories of Machine Learning

Segment 7 - Supervised Learning, Linear Regression 1

Segment 8 - Supervised Learning, Linear Regression 2

Segment 9 - Supervised Learning, Linear Regression 3

Segment 10 - Supervised Learning, Linear Regression 4

Segment 11 - Supervised Learning, Bayes Theorem

Segment 12 - Supervised Learning, Naive Bayes

Segment 13 - Supervised Learning, Support Vector Machines (SVM) Introduction

Segment 14 - Supervised Learning, SVMs

Segment 15 - Unsupervised Learning, K-Means

Segment 16 - Reinforcement Learning

Segment 17 - Supervised Learning, Deep Learning

Segment 18 - Rick Rashid, Natural Language Processing

Segment 19 - Deep Learning, Hearing Aid

Segment 20 - Machine Learning in IIoT

Segment 21 - Machine Learning Summary

Module 3 Quiz

Introduction

Segment 1 - Learning Outcomes, Definition of Big Data

Segment 2 - Importance of Big Data, Characteristics of Big Data

Segment 3 - Size of Big Data

Segment 4 - Introduction to Predictive Analytics

Segment 5 - Role of Statistics and Data Mining

Segment 6 - Machine Learning, Generalization and Discrimination

Segment 7 - Frameworks, Testing and Validating

Segment 8 - Bias and Variance in your Data

Segment 9 - Out-of-sample Data and Learning Curves

Segment 10 - Cross Validation

Segment 11 - Model Complexity, Over- and Under-fitting

Segment 12 - Processing Your Data Prior to Machine Learning

Segment 13 - Good Data, Smart Data

Segment 14 - Visualizing Your Data

Segment 15 - Principal Component Analysis (PCA)

Segment 16 - Prognostic Health Management, Hadoop Machine Learning Library

Segment 17 - My Example: Predicting NFL Football Winners

Segment 18 - Tom Bradicich, Hewlett Packard's Viewpoint on Big Data

Module 4 Quiz