Innledning

Students will gain advanced knowledge of key theories and concepts of big data and machine learning. They will acquire specialised problem-solving skills, being able to bring together several key technologies used in manipulating, storing, and analysing big data. They shall take responsibility to conduct the planning and implementation of activities and evaluate the organisations value of big data.

Students will learn how to extract and identify useful features that best represent the data, learn about the most important machine learning algorithms as well as evaluating the performance of the chosen machine learning algorithm.

Læringsutbytte

Knowledge 

The student...

  • is able to demonstrate thorough knowledge of the theoretical and practical concept of big data
  • is able to demonstrate advanced knowledge of methods and tool for manipulating, storing and analysing big data

Skills 

The student...

  • is able to use Hadoop and related tools that provide easy access to large data volumes, well suited to capturing the value of big data
  • is able to analyze NoSQL storage solutions such as HBase, Cassandra, Oracle NoSQL or similar, for their critical features
  • is able to examine memory resident databases and streaming technologies which allow analysis of data on the flight
  • is able to use machine learning techniques to exploit the opportunities hidden in big data

General competence 

The student...

  • is able to design highly scalable systems that can accept, process, store, and analyse large volumes of unstructured data in (near) real time
  • is able to critically evaluate ethical issues related to big data
  • is able to design a system to organize data, uncover patterns and insights, make predictions using machine learning, and communicate the results

Emnet inngår i

Master in Applied Computer Science

Læringsaktiviteter

Block mode

Anbefalt tidsbruk

Lectures and student guidance: 36 hours

Self-study: 76 hours

Preparation for presentation/discussion in class: 25 hours

Exercise: 45 hours

Assessment: 18 hours

Total: 200 hours

Eksamen

Exam type 1: Individual written home examination*

Duration: 3 weeks

Grading scale: Norwegian grading system using the graded scale A - F where A is the best grade, E is the lowest pass grade and F is fail 

Weighting: 75 % of the overall grade 

Support materials: All support materials are allowed 

 

Exam type 2: Individual written examination

Duration: 2 hours 

Grading scale: Norwegian grading system using the graded scale A - F where A is the best grade, E is the lowest pass grade and F is fail 

Weighting: 25 % of the overall grade 

Support materials: No support materials are allowed

Kontinuasjon

*Resit home examination: New assignment with a duration of 10 days.