Study Guide

Objective

- Introduktion till Big Data
- How to design and implement a data collection system
- How to present data from a business viewpoint

Content

- Node.js
- Azure Stream analytics
- Azure Big Data

Location and time

Autumn, Vasa

Materials

Moodle

Teaching methods

The course is based on lectures, self-study and exercises in a classroom environment. The labs are compulsory

Exam schedules

Autumn

Student workload

About 50% attendance studies and about 50% self-study

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

At least 10p/30p.

Assessment criteria, good (3)

At least 18p/30p.

Assessment criteria, excellent (5)

At least 26p/30p.

Assessment methods and criteria

Of the marks of the examination questions, you must obtain at least 33% in order to obtain a grade in the course, irrespective of the total score of the exams. 33% for pass, per exam. In total, 33% is applied for approved and linear scale.

Assessment criteria, satisfactory (1-2)

At least 10p/30p

Assessment criteria, good (3-4)

At least 18p/30p

Assessment criteria, excellent (5)

At least 26p/30p

Qualifications

Data Management
Full-stack project
AI programming