The MOOC http://mooc.sending-project.eu has been developed in the context of the Erasmus+ project SEnDIng. It aims to provide ICT professionals with knowledge and skills at the Data Science and Internet of Things domains. It contains 6 Data Science courses and 6 Internet of Things courses.
DATA SCIENCE ONLINE COURSES
DS-EM1: Introduction to Data Science. In this course you will be introduced to Data Science and its applications. The aim of the course is to understand what the Data Science is, and the various activities that perform the different roles involved in Data Science projects. You will learn which the different phases of solving a Data Science problem are, well-known tools and frameworks utilized, as well as Data Science applications at different domains.
DS-EM2: Applied Machine Learning. In this course you will be introduced to the concept of Machine Learning and its applications in various domains. The aim of the course is to give you a comprehensive overview of Machine Learning and to assist you in understating what Machine Learning is, how Machine Learning algorithms work and how they could be utilized in solving real world problems. In addition, you will learn toolkits to design and formulate Machine Learning methods.
DS-EM3: Python for Data Science. In this course you will be introduced to the concept of Machine Learning and its applications in various domains. The aim of the course is to give you a comprehensive overview of Machine Learning and to assist you in understating what Machine Learning is, how Machine Learning algorithms work and how they could be utilized in solving real world problems. In addition, you will learn toolkits to design and formulate Machine Learning methods. At the end of the course, you will be asked to complete quizzes to apply your newly acquired skills and knowledge.
DS-EM4: Storing and Retrieving Data. In this course you will be introduced to the Hadoop ecosystem for storing and processing large volumes of data distributed across commodity servers. You will be equipped with the theoretical and practical background needed to perform Hadoop routine tasks and troubleshoot Hadoop clusters. Furthermore, the fundamentals of MapReduce and Spark Framework will be presented. Completing this course, you will be able to administrate and establish a secure Hadoop environment and work with the common Hadoop-related processing frameworks and modules.
DS-EM5: Statistics for Data Science. This course consists an introduction to R programming language for solving Data Science problems. The aim of the course is to become familiar with R programming language and its libraries and packages for inferential statistical analysis, visualization and for implementing machine learning algorithms.
DS-EM6: Data Visualization. In this course you will be introduced to Data Visualization and its applications in order to enhance visual communication. You will be equipped with the theoretical and practical tools needed to build effective and engaging data visualizations. Additionally, the role of the Data Scientist from a data presentation and communication perspective will be defined. Completing this course, you will be able to design and develop visual stories with data, discover trends and patterns, and potentially communicate their findings to a non-technical or broader audience.
INTERNET OF THINGS ONLINE COURSES
IoT-EM1: Introduction to IoT. This course consists an introduction to the IoT concept and its applications. It aims to make you familiar with the IoT technology and present the different roles involved in an IoT project. In addition it presents common IoT application development tools and methods.
IoT-EM2: Architectural Design and Applications in IoT. This course provides an introduction to the key aspects of an IoT system architecture with emphasis on cloud computing solutions (service models, deployment models, public cloud providers and services). Furthermore, it presents the non-functional requirements that should be taken into account when designing IoT applications, followed by the software architectural styles in IoT applications (client-server, peer-to-peer, publish-subscribe, etc.) and how they relate to the aforementioned quality attributes. Moreover, the course provides an overall recommended architecture for IoT solutions in terms of core and optional subsystems along with a discussion of cross-cutting concerns for IoT applications.
IoT-EM3: IoT Communication Technologies. This course presents well-known communication protocols and standards used for signaling and data exchange in IoT systems. Special emphasis is given on the main characteristics, features and metrics of each protocol and standard. The relationship between the traditional TCP/IP protocol stack with the IoT protocol stack is presented and explained. Moreover, a comparison between different IoT communication technologies is done aiming to support you for selecting the right communication protocol for different IoT applications.
IoT-EM4: IoT Security and Privacy. The course introduces the security challenges and risks faced in the IoT ecosystem, given that the IoT may is the most unsecure network encounter so far. In addition, it presents measures to create a more secure IoT environment and protect it from various threats. The course aims to create you a sense of awareness of the possible security breaches in IoT and how to avoid them by adapting appropriate security measures whenever possible.
IoT-EM5: IoT Devices. This course introduces the “Things” in the Internet of Things. It deals with the different categories of IoT devices (sensors, actuators, peripherals), their electronics, as well as, the different microcontrollers and how they can interact with the IoT environment. The course focuses on how to select and interface common sensors and actuators to support IoT applications.
IoT-EM6: IoT Business Value. This course is an introduction to the IoT business value. You will initially see how a company can be transformed with the use of IoT, by presenting common IoT applications in various business domains. Then, the different IoT business model types and challenges that arise in an enterprise will be presented. Finally, various case studies of companies successfully adopted IoT based strategies will be presented.
The access to MOOCs is open and free to anyone interested to build his/her knowledge and skills at the Data Science and IoT domains!