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Data Structures and Algorithms with PythonLaajuus (5 cr)

Code: TX00FK26

Credits

5 op

Teaching language

  • English

Responsible person

  • Janne Salonen

Objective

After completing the course, student has ability to make comparisons about which data structure and/or algorithm is good for certain programming tasks. She/he has gained ability to use data structures and algorithms in her/his programming.

Content

- Python data types and structures (A Python brief summary)
- Algorithm performance basics and arrays
- Lists
- Stacks and queues
- Trees
- Hashing
- Graphs
- Priority queues and heaps, searching
- Sorting
- Algorithms' design techniques

Assessment criteria, satisfactory (1)

- Passed Exam

Enrollment

02.07.2024 - 31.07.2024

Timing

01.08.2024 - 31.07.2025

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

School of ICT

Campus

Karaportti 2

Teaching languages
  • English
Degree programmes
  • Information and Communication Technology
Teachers
  • Janne Salonen
Teacher in charge

Janne Salonen

Groups
  • VIOPE_NonStop7
    VIOPE_NonStop7

Objective

After completing the course, student has ability to make comparisons about which data structure and/or algorithm is good for certain programming tasks. She/he has gained ability to use data structures and algorithms in her/his programming.

Content

- Python data types and structures (A Python brief summary)
- Algorithm performance basics and arrays
- Lists
- Stacks and queues
- Trees
- Hashing
- Graphs
- Priority queues and heaps, searching
- Sorting
- Algorithms' design techniques

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

- Passed exam

Timing

16.04.2024 - 31.12.2025

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

School of ICT

Campus

Karaportti 2

Teaching languages
  • English
Seats

0 - 5000

Degree programmes
  • Information and Communication Technology
Teachers
  • Virve Prami
Teacher in charge

Janne Salonen

Groups
  • ATX25TV_MAKSULLINEN_JÄRJESTELMÄ
    Open UAS 2025
  • ATX24TV_MAKSULLINEN_JÄRJESTELMÄ
    ATX24TV Open UAS

Objective

After completing the course, student has ability to make comparisons about which data structure and/or algorithm is good for certain programming tasks. She/he has gained ability to use data structures and algorithms in her/his programming.

Content

- Python data types and structures (A Python brief summary)
- Algorithm performance basics and arrays
- Lists
- Stacks and queues
- Trees
- Hashing
- Graphs
- Priority queues and heaps, searching
- Sorting
- Algorithms' design techniques

Location and time

Course environment is Metropolia's Moodle environment and course can be done in own pace.

Materials

Online.

Teaching methods

Course is 100% online (self-study) course which can be done in own pace.

Employer connections

N/A

Exam schedules

Online in course pace.

International connections

N/A

Completion alternatives

N/A

Student workload

Depends on the student's starting level.

Content scheduling

Up to student her-/himself.

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

- Passed exam

Assessment methods and criteria

Pass after all of tasks and Final has been approved.

Timing

01.01.2024 - 31.12.2025

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

School of ICT

Campus

Karaportti 2

Teaching languages
  • English
Seats

0 - 5000

Degree programmes
  • Information and Communication Technology
Teacher in charge

Janne Salonen

Groups
  • ATX24TV
    NonStop virtual studies year 2024

Objective

After completing the course, student has ability to make comparisons about which data structure and/or algorithm is good for certain programming tasks. She/he has gained ability to use data structures and algorithms in her/his programming.

Content

- Python data types and structures (A Python brief summary)
- Algorithm performance basics and arrays
- Lists
- Stacks and queues
- Trees
- Hashing
- Graphs
- Priority queues and heaps, searching
- Sorting
- Algorithms' design techniques

Location and time

Course environment is Metropolia's Moodle environment and course can be done in own pace.

Materials

Online.

Teaching methods

Course is 100% online (self-study) course which can be done in own pace.

Employer connections

N/A

Exam schedules

Online in course pace.

International connections

N/A

Completion alternatives

N/A

Student workload

Depends on the student's starting level.

Content scheduling

Up to student her-/himself.

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

- Passed exam

Assessment methods and criteria

Pass after all of tasks and Final has been approved.

Timing

01.01.2024 - 31.07.2025

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

School of ICT

Campus

Karaportti 2

Teaching languages
  • English
Seats

0 - 5000

Degree programmes
  • Information and Communication Technology
Teacher in charge

Janne Salonen

Groups
  • ATX24TV_MAKSULLINEN_JÄRJESTELMÄ
    ATX24TV Open UAS

Objective

After completing the course, student has ability to make comparisons about which data structure and/or algorithm is good for certain programming tasks. She/he has gained ability to use data structures and algorithms in her/his programming.

Content

- Python data types and structures (A Python brief summary)
- Algorithm performance basics and arrays
- Lists
- Stacks and queues
- Trees
- Hashing
- Graphs
- Priority queues and heaps, searching
- Sorting
- Algorithms' design techniques

Location and time

Course environment is Metropolia's Moodle environment and course can be done in own pace.

Materials

Online.

Teaching methods

Course is 100% online (self-study) course which can be done in own pace.

Employer connections

N/A

Exam schedules

Online in course pace.

International connections

N/A

Completion alternatives

N/A

Student workload

Depends on the student's starting level.

Content scheduling

Up to student her-/himself.

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

- Passed exam

Assessment methods and criteria

Pass after all of tasks and Final has been approved.

Timing

01.01.2024 - 31.07.2024

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

School of ICT

Campus

Karaportti 2

Teaching languages
  • English
Degree programmes
  • Information and Communication Technology
Teachers
  • Janne Salonen
Teacher in charge

Janne Salonen

Groups
  • VIOPE_NonStop6
    VIOPE_NonStop6

Objective

After completing the course, student has ability to make comparisons about which data structure and/or algorithm is good for certain programming tasks. She/he has gained ability to use data structures and algorithms in her/his programming.

Content

- Python data types and structures (A Python brief summary)
- Algorithm performance basics and arrays
- Lists
- Stacks and queues
- Trees
- Hashing
- Graphs
- Priority queues and heaps, searching
- Sorting
- Algorithms' design techniques

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

- Passed exam

Timing

01.01.2024 - 31.07.2024

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

School of ICT

Campus

Karaportti 2

Teaching languages
  • English
Degree programmes
  • Information and Communication Technology
Teachers
  • Janne Salonen
Teacher in charge

Janne Salonen

Groups
  • Viope_nonstop_9
    Viope_nonstop_9

Objective

After completing the course, student has ability to make comparisons about which data structure and/or algorithm is good for certain programming tasks. She/he has gained ability to use data structures and algorithms in her/his programming.

Content

- Python data types and structures (A Python brief summary)
- Algorithm performance basics and arrays
- Lists
- Stacks and queues
- Trees
- Hashing
- Graphs
- Priority queues and heaps, searching
- Sorting
- Algorithms' design techniques

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

- Passed exam

Timing

01.01.2024 - 31.07.2024

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

School of ICT

Campus

Karaportti 2

Teaching languages
  • English
Degree programmes
  • Information and Communication Technology
Teachers
  • Janne Salonen
Teacher in charge

Janne Salonen

Groups
  • Viope_nonstop_11
    Viope_nonstop_11

Objective

After completing the course, student has ability to make comparisons about which data structure and/or algorithm is good for certain programming tasks. She/he has gained ability to use data structures and algorithms in her/his programming.

Content

- Python data types and structures (A Python brief summary)
- Algorithm performance basics and arrays
- Lists
- Stacks and queues
- Trees
- Hashing
- Graphs
- Priority queues and heaps, searching
- Sorting
- Algorithms' design techniques

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

- Passed exam

Timing

01.01.2024 - 31.07.2024

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

School of ICT

Campus

Karaportti 2

Teaching languages
  • English
Degree programmes
  • Information and Communication Technology
Teachers
  • Janne Salonen
Teacher in charge

Janne Salonen

Groups
  • Viope_nonstop_12
    Viope_nonstop_12

Objective

After completing the course, student has ability to make comparisons about which data structure and/or algorithm is good for certain programming tasks. She/he has gained ability to use data structures and algorithms in her/his programming.

Content

- Python data types and structures (A Python brief summary)
- Algorithm performance basics and arrays
- Lists
- Stacks and queues
- Trees
- Hashing
- Graphs
- Priority queues and heaps, searching
- Sorting
- Algorithms' design techniques

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

- Passed exam

Timing

01.01.2024 - 31.07.2024

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

School of ICT

Campus

Karaportti 2

Teaching languages
  • English
Degree programmes
  • Information and Communication Technology
Teachers
  • Janne Salonen
Teacher in charge

Janne Salonen

Groups
  • Viope_nonstop_13
    Viope_nonstop_13

Objective

After completing the course, student has ability to make comparisons about which data structure and/or algorithm is good for certain programming tasks. She/he has gained ability to use data structures and algorithms in her/his programming.

Content

- Python data types and structures (A Python brief summary)
- Algorithm performance basics and arrays
- Lists
- Stacks and queues
- Trees
- Hashing
- Graphs
- Priority queues and heaps, searching
- Sorting
- Algorithms' design techniques

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

- Passed exam

Timing

01.01.2024 - 31.12.2027

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

School of ICT

Campus

Karaportti 2

Teaching languages
  • English
Seats

0 - 10000

Degree programmes
  • Information and Communication Technology
Teachers
  • Janne Salonen
Teacher in charge

Janne Salonen

Groups
  • IT_path_180_ects
    Information Technology, Open path 180 ECTS

Objective

After completing the course, student has ability to make comparisons about which data structure and/or algorithm is good for certain programming tasks. She/he has gained ability to use data structures and algorithms in her/his programming.

Content

- Python data types and structures (A Python brief summary)
- Algorithm performance basics and arrays
- Lists
- Stacks and queues
- Trees
- Hashing
- Graphs
- Priority queues and heaps, searching
- Sorting
- Algorithms' design techniques

Location and time

Online, self-study course.

Materials

Online.

Teaching methods

Course is 100% online (Self-Study) course which can be done in own pace.

Employer connections

N/A

Exam schedules

Online.

International connections

N/A

Completion alternatives

N/A

Student workload

Up to Student her-/himself.

Content scheduling

Up to Student her-/himself.

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

- Passed exam

Enrollment

02.07.2023 - 31.07.2023

Timing

01.08.2023 - 31.07.2024

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

School of ICT

Campus

Karaportti 2

Teaching languages
  • English
Degree programmes
  • Information and Communication Technology
Teachers
  • Janne Salonen
Teacher in charge

Janne Salonen

Objective

After completing the course, student has ability to make comparisons about which data structure and/or algorithm is good for certain programming tasks. She/he has gained ability to use data structures and algorithms in her/his programming.

Content

- Python data types and structures (A Python brief summary)
- Algorithm performance basics and arrays
- Lists
- Stacks and queues
- Trees
- Hashing
- Graphs
- Priority queues and heaps, searching
- Sorting
- Algorithms' design techniques

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

- Passed exam

Timing

01.08.2023 - 31.12.2023

Number of ECTS credits allocated

5 op

Virtual portion

5 op

Mode of delivery

Distance learning

Unit

School of ICT

Campus

Karaportti 2

Teaching languages
  • English
Seats

0 - 5000

Degree programmes
  • Information and Communication Technology
Teacher in charge

Janne Salonen

Groups
  • ATX23TV_SYKSY
    Open UAS TestOut and Moodle courses

Objective

After completing the course, student has ability to make comparisons about which data structure and/or algorithm is good for certain programming tasks. She/he has gained ability to use data structures and algorithms in her/his programming.

Content

- Python data types and structures (A Python brief summary)
- Algorithm performance basics and arrays
- Lists
- Stacks and queues
- Trees
- Hashing
- Graphs
- Priority queues and heaps, searching
- Sorting
- Algorithms' design techniques

Location and time

Course environment is Metropolia's Moodle environment and course can be done in own pace.

Materials

Online.

Teaching methods

Course is 100% online (self-study) course which can be done in own pace.

Employer connections

N/A

Exam schedules

Online in course pace.

International connections

N/A

Completion alternatives

N/A

Student workload

Depends on the student's starting level.

Content scheduling

Up to student her-/himself.

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

- Passed exam

Assessment methods and criteria

Pass after all of tasks and Final has been approved.