Programplaner og emneplaner - Student
STKD6500 Data Science for Social Innovations I Course description
- Course name in Norwegian
- Data Science for Social Innovations I
- Study programme
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International Summer School - Faculty of Technology, Art and Design
- Weight
- 5.0 ECTS
- Year of study
- 2019/2020
- Programme description
- Course history
-
Introduction
The knowledge obtained in this course can be used to understand better our world (e.g., following the scientific approach). For example, natural environments (the sciences), social interactions, and engineering systems are often complex, and the underlying causal models are difficult to understand. Data-driven modeling and hypothesis generation is essential for understanding system behavior and interactions.
The last decade or so has seen sizable decreases on costs to gather, store, and process data, creating a fertile environment for the use of data analytics approaches to problem solving based on big-data. Examples are: Increasing productivity and efficiency in business domains by guiding decision processes, improving the experience and interaction between the users and systems, or optimizing different environments (e.g., living space, energy footprint).
In the business domains, big-data analytics can support an increase on productivity or efficiency, by guiding decision processes. Similarly, in interactive and ubiquitous environments, big-data analytics can influence the interaction between the system and the users, to improve their experience (e.g., UX, user engagement), or to optimize their environment (e.g., living space, energy footprint).
In health and human welfare, data analytics is key to cost efficiencies and sustainability of the healthcare infrastructure, as well as a represents a promising approach for devising prognostic interventions and novel therapies.
This course is aimed at teaching students about a set of tools and techniques that are state-of-the-art and commonly used for data analytics in the industry.
Recommended preliminary courses
Individual multiple choice home exam over 24 hours.
The exam is only given in English.
Required preliminary courses
One half year of university studies (30 ECTS), in addition to the OsloMet International Summer School's general requirement. The requirement needs to be met by application deadline.
Learning outcomes
After completing this course the student should have the following learning outcome:
Knowledge
On successful completion of this course the student has knowledge of:
- the potential of data analytics for solving different real-life problems
- modern analytics (methods and tools) for building real-world data analytics applications
Skills
On successful completion of this course the student has the ability to:
- apply data analytics to formulate a hypothesis, collect data, analyze it and reach conclusions about the data
- plan and design a real-world data analytics application
- identify and define a problem and craft a solution using data analytics
General Competence
On successful completion of this course the student can apply:
- data analytics principles
- methods/tools for data analytics and data visualization
Teaching and learning methods
The course is organized around a series of lectures, workshops, and a project. The lectures will cover the key topics for the course. The workshops will provide some hands-on experience on the key topics introduced during lectures. The project will help to consolidate the knowledge acquired during the course. The students are expected to attend all the lectures. The project will be focused on solving a real-world problem. The solution will be presented at the end of the course.
Course requirements
The following required coursework must be approved before the student can take the exam:
- An analytics project where a problem is defined and data chosen to solve/answer the problem. The analytics project is to be completed individually or in groups of up to five students.
Assessment
Examination system:
Oral examination. An oral presentation based on the analytics project completed as part of the coursework requirements. The oral presentation will be completed individually or in groups of up to five students, at the end of the summer school. The presentation should include the demonstration of the data analytics application based on the project, and the student(s) need(s) to deliver the PowerPoint presentation and/or any other supportive material prior the presentation. The analytics project and the oral presentation counts for 100% of the final grade.
The oral presentation cannot be appealed.
Permitted exam materials and equipment
Digital competence is a key factor in ensuring the employability of candidates in all professions vital to our society. This course will provide a fundamental understanding of our digital world. It gives an overview of how technology affects our lives and the way we work, as well as our social structures, work patterns and individual preferences contributing to shaping technology. Social media, digital governance, and eHealth are all examples of how technology has profoundly changed our everyday lives in the last few decades. An understanding of the benefits and limitations of technology is vital in any profession, regardless of field or speciality. In this course, students will acquire the basic knowledge required to harness the potential of technology and recognise its limitations and potentially harmful consequences on work and society. They will learn to identify the opportunities to use technology to foster inclusion and participation in an increasingly diverse and multicultural society. They will practice communicating orally the concepts they acquire in a structured manner.
This course is given in English.
Grading scale
After completing this course the student should have the following learning outcome:
Knowledge
On successful completion of this course the student understands:
- the role of technological innovation with regards to consumption, economic growth and sustainable development
- the idea of digital citizenship, including digital rights and responsibilities, from a local, national and global perspective
- the democratic principles behind e-inclusion and a universally designed society
- the basics of information security, including precautions to guarantee safety and privacy
- the basic ideas behind of algorithms, and how their use may constrain or enable work processes and other aspects of everyday life
Skills
On successful completion of this course the student can:
- evaluate and discuss technological and societal aspects of a case in a specific domain
- describe and discuss ethical challenges at the intersection of technology and society, including issues of integration, participation and multiculturalism
- identify, respond to and limit the negative impact of unethical and harmful online behaviour
- evaluate the possibilities and challenges of technological solutions in various professions relevant to their field of study
General Competence
On successful completion of this course the student can:
- be a valuable contributor to the design, planning and implementation of new technology
- be a positive agent of change in their own profession and field of study with regards to leveraging the potential of technology
- participate in innovative processes involving new and emerging technologies and build skills in anticipating and adapting to technological change
- reflect on technology use both within their field and from an interdisciplinary perspective
Examiners
5 group submissions
Overlapping courses
All support materials are allowed for the final exam