Study Guide

Objective

The student can use the features of cloud computing services in application development. The student has basic knowledge of different cloud computing services and their features. The student can select a suitable cloud computing service, which can be used for data management, image recognition, text processing, video processing and other purposes.

Content

- What is cloud computing
- Deploying a cloud computing service
- Image recognition using a cloud computing service
- Text processing and analysis
- Application development on a cloud computing service
- Data management on a cloud computing service
- Comparison of different cloud computing services

Materials

All needed materials will be collected in the Moodle workspace. New material will be added from the internet as needed, due to the nature of cloud services and their rapid development rate.

Documentations and tutorials of used cloud services, for example,Google Cloud / Azure etc.

Teaching methods

Lectures and workshops. Practical exercises in classroom.

Content scheduling

- Cloud computing in general
- Common cloud environments
- Basics of natural language processing (NLP)
- Machine learning in NLP
- Machine learning coding in the cloud
- Other cloud omputing related tools

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student knows the principles of cloud computing and knows how use the basic cloud computing features in simple applications.

Assessment criteria, good (3)

The student knows the principles of cloud computing and knows how use different cloud computing features in application development. The student can select the most pertinent cloud computing service for the given task.

Assessment criteria, excellent (5)

The student can use different cloud computing services in application development. The student can select most suitable cloud computing services for the given task. The student can effectively use the different features of cloud computing services.

Assessment methods and criteria

The course will be graded based on exercises done (portfolio), both the quality, quantity and overall challenge will be taken into account. A final report is also required. Semester project will also affect grading positively.