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Have you ever heard about Internet of Things devices? Of course, you have. Maybe you also have a Raspberry PI in your house monitoring the temperature and humidity. IoT devices are everywhere around us, collecting data about our environment. You will be analyzing Environmental data, Traffic data as well as energy counter data. Following the course, you will learn how to collect and store data from a data stream. You will prepare IoT data for analysis, analyze and visualize IoT data, before implementing a simple machine learning model to take action when certain events occur and deploy this model to a real-time data stream.
Accessing IoT DataFree
In this chapter, you will first understand what IoT data is. Then, you learn how to aquire IoT data through a REST API and using an MQTT data stream to collect data in real time.
Processing IoT data
In the second chapter, you will look at the data you gathered during the first chapter. You will visualize the data and learn the importance of timestamps when dealing with data streams. You will also implement caching to an MQTT data stream.Perform EDA50 xpLine plots100 xpHistogram Plot100 xpClean Data50 xpDealing with missing data50 xpMissing data100 xpMissing data II100 xpGather minimalistic incremental data50 xpWhich timestamp?50 xpCache Datastream100 xpDate and Time100 xpPrepare and visualize incremental data50 xpPivoting50 xpReformat data100 xpAnalyzing Energy counter data100 xp
Analyzing IoT data
In this chapter, you will combine multiple datasoures with different time intervals. You will then analyze the data to detect correlations, outliers and trends.
Machine learning for IoT
In this final chapter, you will use the data you analyzed during the previous chapters to build a machine learning pipeline. You will then learn how to implement this pipeline into a data stream to make realtime predictions.Prepare data for machine learning50 xpTrain/Test split100 xpLogistic Regression100 xpScaling data for machine learning50 xpModel performance100 xpScaling100 xpScaling II100 xpDevelop machine learning pipeline50 xpCreating Pipelines100 xpStore Pipeline100 xpApply a machine learning model50 xpModel predictions100 xpApply model to data stream100 xpWrapping up50 xp
PrerequisitesData Manipulation with pandas
Matthias is an IT Developer with over 10 years of experience in analyzing data and developing data Pipelines for different kinds of data. His responsabilities include developing and maintaining data Pipelines, as well as supporting the business to gather insights from the collected data and finding new ways to combine different data sources.
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I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.
Devon Edwards Joseph
Lloyds Banking Group
DataCamp is the top resource I recommend for learning data science.
Harvard Business School
DataCamp is by far my favorite website to learn from.
Decision Science Analytics, USAA