Basic skills for Data ManagementLaajuus (5 op)
Tunnus: TT00CN80
Laajuus
5 op
Osaamistavoitteet
After completing the course the student can:
- Describe how data can be managed and processed
- Describe how data can be stored in various places and formats
- Manage and analyze data with suitable tools
- Utilize data management tools to process data
- Understand and describe how mathematics can be used for data management
Sisältö
Introduction to data management
Data storage formats
Data storage
Introduction to data processing
Linear algebra
Data management tools
Ilmoittautumisaika
01.06.2024 - 03.09.2024
Ajoitus
03.09.2024 - 13.12.2024
Opintopistemäärä
5 op
Toteutustapa
Lähiopetus
Yksikkö
Tekniikka ja liiketoiminta
Toimipiste
Kupittaan kampus
Opetuskielet
- Englanti
Paikat
30 - 65
Koulutus
- Tieto- ja viestintätekniikan koulutus
- Tietojenkäsittelyn koulutus
Opettaja
- Matti Kuikka
- Tommi Tuomola
Vastuuopettaja
Matti Kuikka
Ajoitusryhmät
- Pienryhmä 1 (Koko: 35. Avoin AMK: 0.)
- Pienryhmä 2 (Koko: 35. Avoin AMK: 0.)
Ryhmät
-
PTIETS23deaiData Engineering and Artificial Intelligence
-
PTIVIS23IData Engineering and Artificial Intelligence
Pienryhmät
- Pienryhmä 1
- Pienryhmä 2
Tavoitteet
After completing the course the student can:
- Describe how data can be managed and processed
- Describe how data can be stored in various places and formats
- Manage and analyze data with suitable tools
- Utilize data management tools to process data
- Understand and describe how mathematics can be used for data management
Sisältö
Introduction to data management
Data storage formats
Data storage
Introduction to data processing
Linear algebra
Data management tools
Oppimateriaalit
Material available via the learning environment (ITS).
Opetusmenetelmät
Weekly contact sessions when 3 hours for theory and practical exercises.
Tenttien ajankohdat ja uusintamahdollisuudet
Exam in Week 49.
Retake exam in January 2025.
Pedagogiset toimintatavat ja kestävä kehitys
The course includes approximately 12 theory sessions and guided exercises sessions where students work with practical tasks.
Around half of the exercises are done during the contact hours.
Additionally, exercises for home work that will be partly demonstrated in during contact sessions.
Opiskelijan ajankäyttö ja kuormitus
Contact hours
- 12 times 1h theory: 12 x 1h = 12 hours (groups together)
- 12 times 2h practice: 12 x 2h = 24 hours (in own group)
- Exam: 2 hours
- 1h Q&A sessions 5-6 times = 5 hours
TOTAL: 43 hours
Home and independent work: approximately 90 hours
Total: approximately: 130 hours
Sisällön jaksotus
Weeks 36 - 48:
Introduction to data management
Introduction to Jupyter Notebook
Data storage formats
Basics of linear algebra (vectors, matrices, linear equations)
Data processing and visualization with Python
Basics of virtualization and Linux shell commands
Introduction to databases
Recap
Week 49: Exam
Viestintäkanava ja lisätietoja
Additional information is share via ITS
Arviointiasteikko
H-5
Arviointimenetelmät ja arvioinnin perusteet
You can achieve points from participation, exercises, participation and exam:
- 20% points from participation
- 50% points from practical exercises in class room and home work
- 30% points from the exam
Assessment:
- Participation and exercise (50% of total to pass): Students must achieve at least 50% of the points to pass the course.
- Exam (50% of total points to pass): Students must achieve at least 50% of the points in order to pass the course.
The course is graded on a scale of 0-5.
Grading will be according to the total points collected by the student during the course as well as the exam.
1: 50% (minimum to pass the course)
2: 60-70%
3: 70-80%
4: 80-90%
5: 90- 100%
Hylätty (0)
Less than 50% points
Arviointikriteerit, tyydyttävä (1-2)
50 - 69% points
Arviointikriteerit, hyvä (3-4)
70 - 89% points
Arviointikriteerit, kiitettävä (5)
At least 90% points
Ilmoittautumisaika
01.06.2023 - 14.09.2023
Ajoitus
04.09.2023 - 15.12.2023
Opintopistemäärä
5 op
Toteutustapa
Lähiopetus
Yksikkö
Tekniikka ja liiketoiminta
Toimipiste
Kupittaan kampus
Opetuskielet
- Englanti
Paikat
25 - 35
Koulutus
- Tietojenkäsittelyn koulutus
Opettaja
- Matti Kuikka
Ryhmät
-
PTIETS22deaiPTIETS22 Datatekniikka ja Tekoäly
-
PTIVIS22IData Engineering and AI
Tavoitteet
After completing the course the student can:
- Describe how data can be managed and processed
- Describe how data can be stored in various places and formats
- Manage and analyze data with suitable tools
- Utilize data management tools to process data
- Understand and describe how mathematics can be used for data management
Sisältö
Introduction to data management
Data storage formats
Data storage
Introduction to data processing
Linear algebra
Data management tools
Oppimateriaalit
Material available via the learning environment (ITS).
Opetusmenetelmät
Weekly contact sessions when 3 hours for theory and practical exercises.
Tenttien ajankohdat ja uusintamahdollisuudet
The exam will be arranged in week 49.
Pedagogiset toimintatavat ja kestävä kehitys
The course includes approximately 12 theory sessions and guided exercises sessions where students work with practical tasks.
Additionally, exercises for home work that will be partly demonstrated in during contact sessions.
Opiskelijan ajankäyttö ja kuormitus
Contact hours
- 12 times 3h theory and practice: 12 x 3h = 36 hours
- Exam: 2 hours
Home work: approximately 90 hours
Total: approximately: 130 hours
Sisällön jaksotus
Week 36 - 48
- Introduction to data management
- Introduction to Jupyter Notebook
- Data storage formats
- Databases
- Git basics
- Data management with Python libraries
- Basics of Linear algebra
- Recap
Week 49:
- Exam
Viestintäkanava ja lisätietoja
ITS.
Arviointiasteikko
H-5
Arviointimenetelmät ja arvioinnin perusteet
The course is graded on a scale of 0-5.
*
You can achieve a maximum of 100 points from practical exercises in class room and home work exercises.
Around half of the exercises are done during the contact hours.
*
Additionally, there is an exam, you need to pass.
Assignments affect to grading 60% and exam 40%.
Hylätty (0)
General: Less than 50 points in exercises and exam not passed (less than 40% points).
Arviointikriteerit, tyydyttävä (1-2)
50 - 69 points in exercises and 40% - 60% points in the exam.
Arviointikriteerit, hyvä (3-4)
70 - 84 points in exercises and 60% - 80% points in the exam.
Arviointikriteerit, kiitettävä (5)
85 - 100 points in exercises and at least 80% points in the exam.