Data Science and IoT learning outcomes

As a first step towards the design of a VET program for Data Science and Internet of Things, SEnDIng has designed the learning outcomes of the vocational trainings. The learning outcomes provide clear requirements about what learners should know and be able to implement in practice at the end of the training cycle. The learning outcomes are compliant with good practices in both the pedagogical theory applicable in VET and the technical domains of IoT and Data Science. They are clear and understandable for all relevant stakeholders involved in the process, namely:

• Companies that represent the industry demand for IoT and Data Science qualified employees,
• Learners who participate in the trainings,
• Educators including VET providers, who design and implement the trainings and
• Policy makers who define the framework of the VET programs.

 The learning outcomes have been designed based on the following procedure:

• Perform a desktop review of existing studies in IoT and Data Science to formulate the scope of the trainings in the respective domains,
• Perform a desktop review of good practices applied for the definition of learning outcomes in VET education and apply them to the process of formulating the learning outcomes of Data Science and IoT vocational trainings,
• Define in close communication with the relevant stakeholders a draft version of the learning outcomes and validate them and
• Formulate the final version of the learning outcomes and continuously improve them during the design and implementation of the trainings. 

The designed learning outcomes for Data Science and IoT vocational trainings are depicted below:

	Knowledge	Skills	Competences
Internet of Things	Describe the value that IoT delivers in different business domains Explain the business processes related to IoT in specific domains; Understand IoT architectures and the related network and communication protocols Recognize different types of sensors, actuators, displays and related embedded electronics Design the application level (e.g. use protocols that support different IoT applications) of IoT in the context of big data, cloud technologies and data science Formulate requirements about IoT information security	Analyse, argue and describe the business value of a particular IoT system Design an IoT system that includes sensors, controllers, actuators and displays, connected to a cloud platform through internet connection Develop and deploy workflows and dashboards for an IoT system that includes sensors, controllers, actuators and displays, connected to a cloud platform through internet connection Develop working code for an IoT system that includes sensors, controllers, actuators and displays, connected to a cloud platform through internet connection Apply IoT information security concepts	Exercise self-management within the guidelines of work or study contexts that are usually predictable, but still are a subject to change Supervise the routine work of others, taking some responsibility for the evaluation and improvement of work or study activities
Data Science	Describe the key concepts of Data Science Describe ICT methods and tools applicable for the storage and retrieval of data Describe methods and tools applicable for the statistical analysis of data Explain basic concepts and requirements related to information security and privacy (e.g. how to deal with people profiling in the context of GDPR)	Analyse domain specific trends and present them as structured information Create code to statistically analyse data Apply data statistics and data visualization Deploy simple machine learning techniques Deploy data storage and retrieval techniques Implement data models validation techniques Ensure that IPR, security and privacy issues are respected	Exercise self-management within the guidelines of work or study contexts that are usually predictable, but are still a subject to change Supervise the routine work of others, taking some responsibility for the evaluation and improvement of work or study activities

As a next step, based on the defined learning outcomes, the project team developed a reference model of skills, e-competences and qualifications needs for Data Science and Internet of Things VET programs. For more information, please refer here.