SMUA4400 Transport Data Analytics Course description

With the development of sensing technologies, transport digitalization generates and provides numerous data from different resources. This course will introduce models and applications of transport systems analysis in the context of transport studies and gain deeper insight into how these models help with the decision‐making process. Topics to be covered include data preprocessing, travel studies and analysis of data; machine learning methods; transportation systems forecast and analyses. Moreover, the course will provide a brief introduction to future sensing technologies and deep learning methods. The methods cover by this course will closely link to real world transport problem, such as travel demand modelling, accessibility, last-mile problem and other related issues.

SYKK1300 and SYKP1300 overlap 100 %.

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and competence:

Knowledge

The student is capable of

• describing different types of medication, administration methods, pharmacokinetics and pharmacodynamics
• describing interactions and side effects of the use of selected drugs
• describing different reasons for variations in the response to drugs
• describing generic drug substitution and applying the Norwegian Medicines Agency's substitution list or local substitution list
• describing the procedure for handling drugs from the drug is prescribed until the patient has taken it or it has been disposed of
• referring to relevant legislation and regulations for the use of drugs, including guidelines for documentation, handling of non-conformities and disposal
• giving an account of the risk of addiction and abuse of drugs

Skills

The student is capable of

• carrying out independent and faultless calculations of drug dosages, quantities and strengths using different methods of administration
• assessing and checking their own and other people’s calculations
• using reference works such as Felleskatalogen and Legemiddelhåndboka

Competence

The student is capable of

• planning and carrying out responsible drug administration and quality assuring the individual patient’s use of drugs

Self-study, lectures, work on assignments in groups at worskshop. Practical assignments in digitale platforms. Simulation in drug calculations and drug administration at the SF-unit.

The following must have been completed and approved in order for a student to take the exam:

• participation at workshops and calculation groups, compulsory attendance of 80 %
• simulation in drug administrations, take place in SF-unit, one day
• reflection assignment based on the simulation with a scope of 1,000 words (+/- 10%).
• multiple choice assignment, qualifying arithmetic problems (100% correct) in the form of multiple choice questions within a set time before the exam.

Two individual assignments must be approved. Students who fail to meet the coursework requirements can be given up to one re-submission opportunity.

1) Project report prepared in groups, (max size 6 students) approx. 15 - 25 pages (excl. appendices), weighted 70%.

2) Oral presentation in the same groups and examination of the project report, weighted 30%.

Grading is individual, which means that grades may differ within each group. Both oral and written examinations can be presented/written in teams. To ensure that individual grading should be possible, each group of students will provide a written and signed statement in where each individual's contribution is clearly stated and explained.

All assessment parts must be awarded a pass grade (E or better) to pass the course.

Assessment parts: 1) can be appealed, 2) cannot be appealed

Calculator handed out by the university.

Pass/fail.

1) Two internal examiners

2) Two internal examiners

External examiners are used regularly.

Chaoru Lu: chaorulu@oslomet.no