Rajaa hakua
Piilota rajaukset
MS00CN47-3003
Being present is mandatory- No online teaching
+ Qualifications/Prerequisites:
Student enrollment in the course will not be accepted by the instructor if they have not passed the following prerequisite courses:
- Python programming skills and skills in utilizing Pandas for data manipulation and NumPy for numerical operations and array handling
- Basic knowledge of probability, statistics, calculus, and linear algebra
- Data Analytics and Machine Learning
MS00CN46-3003
Itslearning and contact classes are the main communication channels used on this course.
The student is required to have a computer capable of running a simple Ubuntu virtual machine.
MS00CN48-3003
+ Qualifications/Prerequisites:
Student enrollment in the course will not be accepted by the instructor if they have not passed the following prerequisite courses:
- Python programming skills and skills in utilizing Pandas for data manipulation and NumPy for numerical operations and array handling
- Basic knowledge of probability, statistics, calculus, and linear algebra
- Data Analytics and Machine Learning
- Components and Application of Artificial Intelligence (familiarity with deep neural networks)
Note: This course is project-based, requiring students to possess knowledge in machine learning and deep learning, specifically in image recognition and Sequential models.
Consequently, it is advisable to enroll in the 'Components and Applications of Artificial Intelligence' course first. In that course, students learn how to employ deep neural networks for real-world projects. This foundational knowledge will better prepare students for the project-based nature of this course
MS00BP16-3025
Lisätietoja antavat ohjaavat opettajat Sirpa Erkkilä-Häkkinen ja Matti kuikka.
Kurssiin liittyvissä asioissa käytetään mielellään ItsLearning-alustan keskustelukanavaa. Muista aina merkitä viestiin, mistä kurssista, tehtävästä ja ryhmästä on kyse.
Kirjaston tiedonhankinnan perusteet -kurssiosuudesta vastaa Henri Aho.
MS00BP40-3152
Online-tapaamiset Zoom-yhteydellä:
- Yhteisen aloituspäivän megatrendityöskentely ma 1.9.2025, Zoom-linkki: https://turkuamk.zoom.us/j/68480741322?pwd=gtFarRBZ0fro3vRjAYLVZD0iTCaoMa.1
- Hackathonin ennakkotapaaminen ke 12.11.2025 klo 10–11, Zoom-linkki: https://turkuamk.zoom.us/j/63668259963
- Master Minds -hackathon ma 24.11.2025 klo 8.30–17 (Zoom-linkki ilmoitetaan myöhemmin).
MS00CN43-3003
Qualifications:
Before taking an "Introduction to Data Engineering and AI Technologies" course, students typically need a foundational understanding of several key areas. Here are the prerequisite courses and topics:
1. Python Programming: Proficiency in basic Python syntax and programming constructs, understanding of Object-Oriented Programming (OOP) concepts.
2. Basic Linear Algebra: Understanding of vectors, matrices, and basic operations on them.
3. Statistics and Probability: Knowledge of descriptive statistics (mean, median, mode, variance, etc.), and familiarity with probability distributions.
Recommended: Data Management: Experience with data manipulation libraries such as Pandas for handling datasets. Data manipulation involves transforming data, cleaning it, organizing it, and preparing it for analysis.
MS00CN44-3003
Course material and assignments in Its Learning and AWS academy.
USE OF ARTIFICIAL INTELLIGENCE REPORTED
Allowed, can be used, must be reported. Artificial intelligence can be used in the creation of outputs, but the student must clearly report its use. Failure to disclose the use of AI will be interpreted as fraud. The use of AI may affect the assessment.