Study Guide

Objectives (course unit)

The student knows the basics of web programming and how to implement the storage and processing of data that supports the IoT system. The student is able to implement a simple web application. The student is able to do statistical calculations from data. The student is familiar with the most common modern techniques of data storage and web programming.

Content (course unit)

Web programming (6 ECTS): Web programming techniques and languages, data reading from api, data processing, data display to end user. Command line basics.

Basics of statistics and its concepts (2 ECTS).

Prerequisites (course unit)

Basics of Programming

Assessment criteria, satisfactory (1-2) (course unit)

The student is able to produce a simple web page and format the structure of the page. The student knows statistical key figures.

Assessment criteria, good (3-4) (course unit)

The student is able to create a versatile web application and take advantage of APIs. The student knows and can use statistical key figures.

Assessment criteria, excellent (5) (course unit)

The student is able to create and publish a web application with an easy-to-use structure. The student is able to store, read, process and display data to the end user. The student can use statistical key figures in presenting data.

Location and time

Schedule in learning environment

Exam schedules

Will be announced in October 2024

Time will be scheduled during the course for completing the larger final assignment.

Retakes and raising grades can be arranged by completing a project and/or extra work.

Assessment methods and criteria

Programming part

Exam is mandatory to pass the programming part of the course and is graded 0 - 5.

Maximum points for the exam is 50 points.

Doing exercises give extra points for the exam:
If you do min 50% of given exercises (points) -> 3 extra points for the exam
If you do min 70% of given exercises (points) -> 6 extra points for the exam
If you do min 90% of given exercises (points) -> 9 extra points for the exam

Normal exam practices:
- Allowed 1 retake to raise exam grade
- Allowed 2 retakes to pass the exam

[ 0, 20] => 0
[21, 26] => 1
[27, 32] => 2
[33, 38] => 3
[39, 44] => 4
[45, 50] => 5


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Math part

Course math part will be held during period 3, i.e., between 8.1.2025-23.2.2025

Math part is evaluated based on the activity and know-how demonstrated on the lessons and by returned assignments by grade 0-5.

Math part points are divided as follows:
Lesson activity: max 12p
Assignments: max 18p

Math part point limits
35%: 1
50%: 2
65%: 3
80%: 4
90%: 5
- - - - - -- - -

The overall course grade will be calculated as a cu-weighted average of Programming part (6/8) and Math parts (2/8).

Assessment scale

0-5

Teaching methods

Lectures
Assignments
Project (larger assignment)
Exam

Learning materials

Online Learning Environment

Student workload

Programming Part
4 hours of classroom lectures per week. (60h)
Independent work (102h)
Homework is the exercises not completed during the lecture.

Math part ca 50 h
~4x2,5h contact teaching
Independent work ca 40 h

Content scheduling

Programming part
Git
HTML
CSS
JavaScript
Node

Math part
Statistical descriptors
Statistical inference
Data visualization

Completion alternatives

Programming part
Complete only the exam

Practical training and working life cooperation

Web development:
Average 4 hours of classroom lectures per week, 60h of lectures.
Homework is the exercises not completed during the lecture.

Math part ca 45 h
3x3h contact teaching
Independent work ca 35 h