Bachelor in Applied Data Science

Bachelor in Applied Data Science

  • Study Facts
    • Area of Study
      Computing
    • ECTS
      180
    • NQF Level
      Bachelor's degree (Level 6 1. Cycle)
    • Campus
      Kristiansand, Online
    • Study Mode
      Full-time, Online
    • Entry Requirements
    • Study Programme Leader
      Isah Lawal
Introduction

Noroff University College (NUC) offers awards that specialise in the utilisation of digital technology. The objective of the Bachelor in Applied Data Science is to provide you with an understanding of the whole life cycle of the data science process, from data acquisition and exploration to analysis and communication of the results. There is an increasing level of commercial interest in this program area as industry seeks to gain the maximum advantage from the intelligent analysis of large unstructured data sets that will allow them to transform data from raw material to product. Thus, Data Scientists are needed across a wide variety of employment sectors including medicine, manufacturing, natural sciences, pharmaceuticals, finance, retail, and engineering. Students will have an opportunity to develop domain expertise in the final year of the degree. Looking at the requirements of the industry sectors of Oil and Gas, Energy, Engineering and Information Technology, and society-related sectors of government and healthcare.

The aim is to help you develop the required skills to extract actionable insight from data and to create data-driven solutions to real-world problems. This information can be used by stakeholders to facilitate their decision-making process and this will encompass the collection of appropriate datasets for a given problem, development of database for data storage and processing, statistical analysis of the data, predictive analytics and data visualization and communication. The degree programme will challenge you to develop a scientific, rigorous approach to your work. This will enable you to not only solve issues posed as part of the course but also to address unforeseen problems once employed as a data scientist or analyst.

After receiving a general background in applied computing, students will develop skills in database development, statistical analysis, machine learning and software development. Throughout the program students build upon this skill set with their own self-motivated research projects, resulting in graduates that are ready for either employment or postgraduate study.

Students also develop a high level of competency in a variety of specific tools and techniques, along with a solid foundation of knowledge, skills, and competence to support them in lifelong learning throughout their careers. They will have several key attributes:

  1.  A deep understanding and practical application of data analytics skill set
  2. Hands-on experience with tools used for data analysis
  3. A high degree of problem-solving skills
  4. A high legal and ethical standard required for data handling
Aims of the Degree Programme

This degree programme aims to develop individuals with the capacity to analyse and understand large data sets and engage in data-driven research and development. Students will have blend of skills and practical experience to become employment-ready graduates with a holistic understanding of both theory and practice in relation to the collection, processing, and analysis of large unstructured data sets.

The core topics addressed in the degree are:

  • Big data analytics (Data analysis of fast-growing, massive, heterogeneous, and complex datasets).
  • Software development (appropriate methodologies and programming languages).
  • Data storage and database technologies (e.g., NoSQL).
  • Mathematics (mathematical and statistical modelling and analysis).
  • Big data visualisation (appropriate visualisation concepts, software, tools and techniques).
  • Artificial intelligence and Machine Learning (theories, technologies, and languages).

Graduates will be able to understand and apply an array of tools and techniques to collect and process very large amounts of data, with the purpose of unlocking and extracting previously unknown knowledge. These skills are required in a wide variety of sectors, including medicine, manufacturing, natural sciences, pharmaceuticals, finance, retail, and engineering. The subject material will enable graduates to go on to postgraduate study in the area and will also enable them to fulfil several distinct employment titles.

Entry Requirements

For general admission it is required to document the following criteria as passed:

  • Higher Education Entrance Qualification, and 
  • Candidates must be able to document proficiency in the English language. Language requirements by Samordna Opptak

Special admission requirements
In addition to the general admission requirements, it is required to document the following:

  • Mathematics R1 (or S1+S2)

For admission on basis of prior learning and work experience:
Admission based on prior experience requires a written application for evaluation. Applicable candidates must be at least 25 years of age in the year of admission.

For candidates with foreign education the requirements for Higher Education are: 

  • The country must be recognized by NOKUT, specified in the GSU-list.
  • Candidates must be able to document proficiency in the English language. Language requirements by Samordna Opptak

For further information, please see the admission requirements: https://www.noroff.no/en/admission/admission-requirements

Campus and Online Study

All students follow the same progression according to their education plan, irrespective of whether they study online or on campus. All students study the courses at the same time, with the same delivery and workload, following identical assessment strategies for every course. At the study level no distinction is therefore made between campus and online students. All students are required to engage in live education sessions (such as lectures) and undertake all required educational activities.

Students are encouraged to interact with each other via online forums and chat systems, enabling discussions to take place involving both online and campus students. Each student cohort is therefore a single learning community, concurrently engaging in all educational activities irrespective of actual physical location. Throughout all educational sessions course staff actively encourage participation from campus and online students simultaneously, and do not focus solely on those who are physically present.

This tight integration of campus and online ensures students will be part of a cohesive learning community throughout their study. As a result, this also means that should students personal situations change during their studies, and they must change their mode of study from online to campus (or vice versa) this can be done with little to no disruption to their studies.

Opportunities for Further Studies

Undertaking some period of study at an international educational institution can result in many benefits to those who take part, including:

  • Language and general competence in the destination country and culture 
  • Development of personal and professional networks in other parts of the world
  • Personal growth and holistic development.

All students are eligible to apply to undertake a period of study at an international university. All international study opportunities are subject to the application processes and admissions requirements of the international institution, in addition to an evaluation of the suitability of the proposed study exchange within the students’ study at NUC. Full details of international study opportunities and the application process is available to all students within the LMS.

Accredited
May 23rd, 2017
Last revision date: 
June 2022