Applied Data Science

Bachelor in

Applied Data Science

Study Online or On Campus in Norway

The programme equips you for a dynamic career, fostering collaboration with businesses to understand and harness the vast amounts of data at their disposal. It also cultivates skills in the field of intelligent AI systems.

Apply now

Online Studies

11 August 2025

3 years full time

NOK 49.000,- per semester
NOK 0,- registration fee

State Educational Loan Fund (Lånekassen)

Online+ Oslo/Bergen

11 August 2025

3 years full time

NOK 55.000,- per semester
NOK 0,- registration fee

State Educational Loan Fund (Lånekassen)

Campus Kristiansand

11 August 2025

3 years full time

NOK 62.000,- per semester
NOK 1.900,- registration fee

State Educational Loan Fund (Lånekassen)

AI in the study programme

How is AI used in the Applied Data Science programme?

The Applied Data Science program integrates AI throughout its curriculum, equipping you with the essential knowledge and skills to excel in the field. Focusing on machine learning, natural language processing, predictive modelling, Big Data, and programming, the courses provide a solid foundation for developing innovative AI applications.

This comprehensive approach ensures you become well-versed in AI technologies and gain experience analysing large datasets to generate data-driven insights, preparing you for opportunities in the evolving AI landscape.

How is AI being used in the workplace as part of Applied Data Science?

AI is revolutionizing the business landscape by changing how data is processed and utilized in decision-making. It enables businesses to make quicker and more precise decisions through sophisticated analytics and automated insights.

The demand for skilled data science professionals who can develop AI solutions is growing rapidly. This program is designed to equip you not just as a user but as a developer of innovative AI solutions, positioning you at the forefront of this emerging field and ensuring you play a vital role in the future of business.

Why Study Applied Data Science?

Data science is a key skill in today's world, with data flowing from sources like social media, e-commerce, sensors, and IoT devices. Companies like Netflix, Spotify, and Google showcase the power of data in creating value. The growing reliance on data makes roles like data analyst highly sought after, offering strong demand and competitive salaries.

This programme teaches you to turn raw data into actionable insights. You’ll gain hands-on expertise in tools and techniques for data management, analysis, visualisation, software development, artificial intelligence, and machine learning.

Career Opportunities

After completing the applied data science program, you can pursue roles such as:

  • AI Specialist
  • Data Analyst
  • Data Scientist
  • Machine Learning Engineer
  • Business Intelligence Analyst
  • Research Scientist
  • Software Developer
Dior Anvarov

Dior's sought-after expertise secured him a job

Programme information

Learning outcomes

The programme combines general computer science with specialised expertise in data science. It covers a wide range of topics including data structures, analysis, visualisation, programming and machine learning.

The first year focuses on building a foundation in technical subjects and developing research and study skills. The second year delves deeper into programming, data structures and statistics. The third year concludes with a bachelor project, where students can apply their skills to innovative projects in a variety of sectors, including oil and gas, engineering, information technology, public administration and healthcare. The programme provides both theoretical and practical knowledge, making you an expert in data science and enabling you to work in different industries.

Read more about the study program in our course catalog.

Course structure

First-year subjects:

  • Problem Based Learning and Research Methodologies (5 ECTS)
  • Introduction to Programming (10 ECTS)
  • Discrete Mathematics (10 ECTS)
  • Programming and Databases (10 ECTS)
  • Network Principles (10 ECTS)
  • Introduction to Information Security (5 ECTS)
  • Studio 1 (10 ECTS)

Second-year subjects:

  • Introduction to Operating Systems (5 ECTS)
  • NoSQL Databases (10 ECTS)
  • Professional Software Development (5 ECTS)
  • Object Oriented Programming (10 ECTS)
  • Algorithm and Data Structure (10 ECTS)
  • Statistical Analysis (10 ECTS)
  • Studio 2 (10 ECTS)

Third-year subjects:

  • Machine Learning (10 ECTS)
  • Big Data Analytics (10 ECTS)
  • Data Visualization (10 ECTS)
  • Elective Courses (2 x 5 ECTS)
  • Bachelor Project (20 ECTS)

Extended programme information

School: Noroff University College
Application deadline: Continuous admission. Applications are processed in the order they are submitted.
Language of instruction: English
Accreditations: Approved for loans and grants from the Norwegian State Educational Loan Fund (Lånekassen). Accredited by NOKUT.
Degree: Bachelor
Credits: 180 ECTS

Equipment Requirements

There are some fundamental differences between the different study modes at Noroff University College (NUC) in relation to hardware and software.

As an Online student, you are responsible for purchasing the required equipment and installing your software. You are also responsible for its maintenance.

As an OnlinePLUS student you will have access to some equipment and resources on your study location, however the equipment you purchase for yourself is your own responsibility and you are responsible for its maintenance.

As a student on Campus Kristiansand, you are provided the required equipment necessary to complete your studies. In addition, you will have access to specialised equipment and tools used within the field of study.

Read detailed equipment requirements here.

Admission requirements

Noroff has ongoing admissions, and applications are processed in the order they are received. The earlier you apply, the earlier you can secure a study place.

To qualify for the program you must have general study competence. It is also possible to apply based on recognized prior learning.

In addition there is a special requirement of Math R1, or S1 and S2, or international equivalent. Other documented knowledge or education can be accepted as equivalent.

For international students, depending upon which country you have received your education from, the requirements will differ. Please use this website where you can find the specific requirements for your country at the bottom of the page.

You can read more about admission requirements here.

Financing

All our study programs are approved for loans and grants from the Norwegian State Educational Loan Fund (Lånekassen). You can apply to the Loan Fund for basic support (loan and grant; NOK 151,690) and tuition fees (NOK 77,192).

As an adult student, you can receive loans and grants from the State Educational Loan Fund. This also applies if you work while studying.

As a main rule, you must be a Norwegian citizen to receive support from the Norwegian State Educational Fund. However, foreign citizens may also be entitled to financial support. Check here to see if you are eligible.

You can read more about payment, loans, and grants here. 

Noroff University College Computing Programmes

A Computing Bachelor's degree from Noroff is your path to high employability. But what exactly are the differences between our four computing degrees in Applied Data Science, Cyber Security, Digital Assurance and Security Management and Digital Forensics and Incident Response?

Bachelor IT Computing at Noroff University College

Student interviews

Benjamin Svendsen
I have gained broad expertise in data, programming, and machine learning. Benjamin Svendsen
Mark Movh
The program covers many areas, which provides many career opportunities. Mark Movh

Our academic staff

Dr. Isah Lawal
Applied Data Science is essential for AI's development and application. It is the key to entering the AI world. Dr. Isah Lawal
Emlyn Butterfield
Data drives the world, it is infinite and people are needed to make sense of it in order to make it useful. Emlyn Butterfield

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