Copenhagen School of Design and Technology

da

IoT and Data Analytics (DA)

2018/2019
Danish title
IoT og dataanalyse (DA)
Study programme
Business Economics & Information Technology
Type of education
Full time education
Level of education
Bachelor Programme
Semester
5. semester
Duration of the subject/module
10 Weeks
Ects
15
Programme elements
Elective
Language
Danish
Start time
Autumn
Location
Lygten 16, København NV
Subject number
9141553
Responsible for the subject(s)/modul(es)
Leif Schwartz Holbek
Kim Juhl
Jesper Skovsgaard Frederiksen
Guillaume Nadon
  • Content and learning outcomes

    Companies in all sizes are these years being pushed to make a Digital Transformation of their business – some sources even states, that companies failing to do it will simply cease to exist in the future.
    Internet of Things (IoT) is one of the new technologies that companies uses to make a digital transformation of and in some industries IoT will simple disrupt the current
    business models. In this elective you will get solid understanding of IoT and insight to what it can be used to. You will be introduced to different IoT Development
    Suites for both IoT devices and back-end systems. This will include programming on different levels, e.g. will Python be introduced, but higher level programming will
    be used as well.
    Data Analytics is another tool for companies in driving their Digital Transformation and have already been used for many years by many companies. IoT will drive this further and in this elective we will look into how to combine IoT and Data Analytics. Data Analytics in various forms will be in focus in this elective.
    The course will give the student deeper knowledge about both IoT and Data Analytics.
    The student will learn about different IoT development suites and systems, and be able to participate in or lead an IoT project in a future job position.
    The student will obtain knowledge about how IoT and Data Analytics can be combined for optimisation or creating new business models.

    Learning goals made simple – a summary
    The course will give the student deeper knowledge about both IoT and Data Analytics.
    The student will learn about different IoT development suites and systems, and be able to participate in or lead an IoT project in a future job position.
    The student will obtain knowledge about how IoT and Data Analytics can be combined for optimisation or creating new business models.

  • Type of instruction
    A mix of theory and practice. There will be lectures followed by case exercises, which will involve cooperation with KEA’s external partners.
    A special emphasis will be put on hands-on experience with programming, IoT Development Suites and Data Analytics tools.
    We will work together with many external partners, have guest speakers and do some company visits to explore some of the current ongoing work in this field out there.
    The elective will be based on hands out and different literature.

    NOTE!
    During the elective there will be two mandatory group case hand-ins. Each of these includes a small report and a class presentation. The two cases will be evaluated and has to be approved before the group/student can take the final elective exam.
  • Subject/module requirement for participation

    Equipment needed to participate
    We assume students to have a laptop that runs Windows 10 (or later) or Mac OS X 10.12 (or later).
    Older versions of Windows or Mac OS and Linux might work in most cases – but is not supported with help to install open source tools or handle teaching examples.
    We assume students have a HDMI-port or miniDVI/lightning port on their laptop.
    In a select few teaching situations (not in 1st semester) examples are used, that does not work well with less than 4 GB RAM Memory – for this 8 GB RAM is recommended.

    Students will need office software (Microsoft, Apple, Google, or..).
    Students need to be able to produce and read pdf-documents, Word-documents, Powerpoint-presentations and Excel-spreadsheets.
    There exist a Microsoft cloud version that becomes available when you set up a free one-drive account.

    An Internet browser needs to be available (i.e. Chrome or Safari).
    We strongly recommend students to have access to Facebook and a private Facebook-account.

  • Exam

    The learning outcomes of the exam are identical with the learning outcomes of the subject(s)/modul(es)

    Prerequisites for access to the examination
    During the elective there will be two mandatory group case hand-ins. Each of these includes a small report and a class presentation. The two cases will be evaluated and has to be approved before the group/student can take the final elective exam.
    Exam in one or more subjects
    Subject/module is tested standalone
    Type of exam
    Written examination
    This elective will be finalized by a hand-in in the form of a written group report which
    is to demonstrate the students’ ability to combine theory and practice.
    Individual exam or group exam
    Group, 2-4 max participants
    Exam languages
    English
    Type of evaluation
    7-point grading scale
    Examiners
    Internal censure
77
hours of teaching
334
hours of preparation
The figure shows the extent of workload related to the subject divided into different study activities.

In the subject IoT and Data Analytics (DA) you will receive 77 hours of instruction, which corresponds to 102 lessons (1 lesson = 45 min.) and 19% of your total workload for the subject.

The teaching primarily consists of the following activities: classroom teaching.
The preparation primarily consists of the following activities: project work.

Read about KEAs Study Activity Model

*KEA can deviate from the number of hours if this is justified by special circumstances