Introduction to IoT is a self-paced, 20-hour course that students can take on their own or it can be offered by an instructor. It provides an overview of the concepts and challenges of the transformational digital economy when people, process, data, and things connect.
Intro to IoT introduces the concept of a network foundation connecting billions of things and trillions of gigabytes of data to enhance decision making and interactions. Course modules describe how IoE drives the convergence between an organization’s operational technology (OT) and information technology (IT) systems, and the business processes for evaluating a problem and implementing an IoE solution. Machine-to-machine (M2M), machine-to-people (M2P), and people-to-people (P2P) connections in an IoE solution are also covered.
The Internet of Things increases the opportunity for people to create and invent new devices due to lower costs and greater access. The resulting explosion of new types of devices and solutions further contributes to the exponential growth of data in the IoT. Organizations are now critically dependent on the collection, storage and analysis of this data to extract information and gain insights for the business. Making good decisions depends on good data. As the amount of data grows, decision makers increasingly rely on data analytics to extract the required information at the right time and in the right place to make the best decision.
Students who complete the Big Data & Analytics course will be able to perform the following functions:
● Explain how businesses can extract information and insights from IoT Data.
● Understand the steps of the Data Analysis Lifecycle and perform these tasks.
● Understand privacy and security aspects of data.
● Explain the different types of data analytics: descriptive, predictive and prescriptive.
● Use Python to create a data pipeline to acquire, manipulate and visualize sensor data.
● Apply exploratory data analysis to extract insights from data.
● Understand how Machine Learning algorithms can be used for predictive analytics.
● Present and communicate using data storytelling.
● Describe the evolution of data management technologies from SQL to NoSQL.
● Understand and explain the evolution of a modern data center computing platform and be aware of distributed scalable Big Data solutions such as Apache Hadoop, Cassandra and Spark.
A breve, l'accesso al LUISS LOFT sarà consentito solo agli studenti in possesso di una tessera di membership. La membership è gratuita e per ottenerla occorre compilare il questionario disponibile all'indirizzo http://tinyurl.com/loftmembership
Per favore, rispondi onestamente! Le tue risposte non saranno oggetto di valutazione, ma ci aiuteranno solo a capire chi sei, cosa ti appassiona e quali sono i tuoi progetti futuri. Ci servirà per strutturare al meglio le attività ed i programmi del LUISS LOFT.
Il questionario può essere compilato sia da smartphone che da computer, in circa 30 minuti. Nei giorni successivi, il team ti contatterà per incontrarti e consegnarti la tessera, che ti consentirà di accedere liberamente allo spazio.
Soon, the access to the LUISS LOFT will be restriceted to members only. The membership is free and you can apply using the following link: http://tinyurl.com/loftmembership
The detailed completion of this questionnaire is necessary in order to obtain the LOFT membership.
Please, be honest! Your answers will not be evaluated, we only need them to understand who you are, what you are passionate about and your future projects.
This will be useful to plan the activities and the programs of the LUISS LOFT in the best possible way.
The questionnaire can be filled in using both a smartphone or a computer, and it will take you about 30 minutes. In the following days, the team will contact you and meet you to hand you your membership card, which will allow you to enter freely in the place.