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Machine Learning services in the cloud (5 cr)

Code: HT00BN67-3002

General information


Enrollment
01.11.2022 - 05.01.2023
Registration for the implementation has ended.
Timing
09.01.2023 - 19.05.2023
Implementation has ended.
Number of ECTS credits allocated
5 cr
Local portion
5 cr
Mode of delivery
Face-to-face
Unit
School of Business
Teaching languages
Finnish
Seats
0 - 30
Degree programmes
Bachelor's Degree Programme in Business Information Technology
Teachers
Juha-Tapio Teno
Groups
HTK21S1
Tietojenkäsittely (AMK)
ZJA23KI
Avoin AMK, tiko
ZJK23KI
Korkeakoulujen välinen yhteistyö, TIKO
Course
HT00BN67
No reservations found for realization HT00BN67-3002!

Evaluation scale

0-5

Objective

Do You Want to learn how to understand cloud services that enable the construction of AI (Artificial Intelligence) and ML (machine learning) services with ready-made models and cloud services? In the course, the students will familiarise and utilise artificial intelligence and machine learning services with image- and optical character recognition and forecasting services in the cloud. The course enables students to understand the potential of cloud-based AI and machine learning services in a digital operating environments.

Course competencies
- Web development competence
- Systems and methods in ICT
- Learning and information management competence

Content

- Artificial intelligence and machine learning services in the cloud.
- document analysis
- forecasting
- image recognition
- other current/relevant AI and machine learning services

Materials

Material written by the teacher can be found at Moodle. Any AWS Academy Learning material or additional machine learning and artificial intelligence books can be used as additional material.

Teaching methods

- Lectures (in-class)
- Contact lessons
- Exercises
- Tests
- Final exam

The primary mode of delivery is a combination of in-class activities on campus. The in-class activities deepen the learning in the forms of tutorials, individual and group works, reflection and guidance.

Exam schedules

The final exam is held at the end of the course. Renewal opportunities will be announced at the end of the course.

Student workload

Approximately 135 hours.

Assessment criteria, satisfactory (1)

Sufficient 1
You have basic knowledge in the area of AI & Machine learning services in the cloud. You know the components and terms of data preprocessing cloud services and what they mean.

Satisfactory 2
You have knowledge in the area of AI & Machine learning services in the cloud. You know the components terms of data preprocessing cloud services and what they mean.

Assessment criteria, good (3)

Good 3
You understand the concepts of AI & Machine learning services in the cloud and can apply the gained knowledge in a real-life data preprocessing problems.

Very good 4
You understand the concepts of AI & Machine learning services in the cloud and can apply the gained knowledge in a real-life AI & Machine learning problems and use cases. You have expanded your knowledge independently during the course.

Assessment criteria, excellent (5)

Excellent 5
In addition to previous requirements you can analytically discuss about the concepts in AI & Machine learning services in the cloud and present and defend (based on knowledge and evidence) your opinions. You can question the presented information and give valid options.

Qualifications

-Web Development Tools
-SQL Basics
-Basics of programming
-Use of command prompt and/or terminal

Further information

Avoin amk 3
EduFutura 5

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