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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 - 09.09.2024

Ajoitus

02.09.2024 - 15.12.2024

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
  • PTIETS23deai
    Data Engineering and Artificial Intelligence
  • PTIVIS23I
    Data 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

Week 49

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
Recap Python
Data storage formats
Basics of linear algebra (vectors, matrices, linear equations)
Data processing with Python
Data visualization with Python
Virtualization?
Introduction to databases
Recap
Week 49: Exam

Viestintäkanava ja lisätietoja

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

Opettaja
  • Matti Kuikka
Ryhmät
  • PTIETS22deai
    PTIETS22 Datatekniikka ja Tekoäly
  • PTIVIS22I
    Data 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.