IoT Fundamentals: Big Data & Analytics

self-learning course



IoT Fundamentals: Big Data & Analytics

Data is everywhere. It can be hard to comprehend how much there is, and how much more new data is generated every day. Data can be the words in a book, the contents of a spreadsheet, pictures, video, audio, or a stream of measurements sent from a monitoring device. Raw data has little useful meaning. We must process this data and then interpret the output to make it useful. This useful data is now information. As this information is applied or understood, it becomes knowledge.

When there is so much data that traditional ways of processing, storing and analyzing it cannot be used, that is called Big Data. Big Data requires new methods and tools to make it meaningful. This course introduces you to those methods and tools to help you to harness the power of Big Data.

Course Outline:

Chapter 0 Course Introduction
0.0 Welcome to IoT Fundamentals: Big Data and Analytics
Chapter 1 Data and the Internet of Things
1.0 Introduction
1.1 Value of Data
1.2 Data and Big Data
1.3 Managing Big Data
Chapter 2 Fundamentals of Data Analysis
2.0 Introduction
2.1 What is Data Analysis?
2.2 Using Big Data
2.3 Data Acquisition and Preparation
2.4 Big Data Ethics
2.5 Preparation for Chapter 2 Internet Meter Labs
Chapter 3 Data Analysis
3.0 Introduction
3.1 Analyzing Data
3.2 Preparation for Chapter 3 Internet Meter Lab
Chapter 4 Advanced Data Analytics and Machine Learning
4.0 Introduction
4.1 Predictive Analytics
4.2 Model Evaluation
4.3 Preparation for Chapter 4 Labs
Chapter 5 Storytelling with Data
5.0 Introduction
5.1 Building a Data Story
5.2 The Power of Visualization
5.3 Preparation for Chapter 5 Labs
Chapter 6 Architecture for Big Data and Data Engineering
6.0 Introduction
6.1 Scaling Data Analytics
6.2 Introduction to Data Engineering
6.3 The Big Data Pipeline
6.4 The Image Processing Labs