Introduction to Data Analytics and Artificial IntelligenceLaajuus (3 cr)
Code: TTC2050
Credits
3 op
Teaching language
- Finnish
- English
Responsible person
- Antti Häkkinen
- Juha Peltomäki
Objective
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Qualifications
Ohjelmoinnin perusteet
Assessment criteria, satisfactory (1)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Assessment criteria, good (3)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Assessment criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Timing
13.01.2025 - 09.02.2025
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Teaching languages
- English
- Finnish
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
ZJA25KTIDA1Avoin amk, Data-analytiikka 1, Verkko
-
ZJA25KTIAvoin AMK, tekniikka, ICT
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Online
Learning materials and recommended literature
Course website (lecture material, exercises, recorded lecture videos)
Teaching methods
Distance learning (exercises, familiarization with lecture material, recorded videos of practical examples)
Student workload
Getting to know the online lecture material 35 hours (recorded lectures with teacher-led exercises)
Distance learning 46 hours (exercises)
A total of 81 hours
Further information for students
The evaluation of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
18.11.2024 - 09.01.2025
Timing
13.01.2025 - 31.03.2025
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- Finnish
Seats
0 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TTV23S2Tieto- ja viestintätekniikka (AMK)
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Weekly guidance for doing exercises in classrooom
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
- Weekly guidance in classroom (students can come to class to do exercises every week and get support for doing the exercises from the teacher)
- Distance learning (students can complete the course at their own pace, doing exercises independently)
Student workload
Distance learning 61h (exercises)
Guidance sessions in class 20h
A total of 81 hours
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
18.11.2024 - 09.01.2025
Timing
13.01.2025 - 31.03.2025
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- Finnish
Seats
0 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TTV23S3Tieto- ja viestintätekniikka (AMK)
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Weekly guidance for doing exercises in classrooom
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
- Weekly guidance in classroom (students can come to class to do exercises every week and get support for doing the exercises from the teacher)
- Distance learning (students can complete the course at their own pace, doing exercises independently)
Student workload
Distance learning 61h (exercises)
Guidance sessions in class 20h
A total of 81 hours
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
18.11.2024 - 09.01.2025
Timing
13.01.2025 - 31.03.2025
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- Finnish
Seats
0 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TTV23S5Tieto- ja viestintätekniikka (AMK)
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Weekly guidance for doing exercises in classrooom
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
- Weekly guidance in classroom (students can come to class to do exercises every week and get support for doing the exercises from the teacher)
- Distance learning (students can complete the course at their own pace, doing exercises independently)
Student workload
Distance learning 61h (exercises)
Guidance sessions in class 20h
A total of 81 hours
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
18.11.2024 - 09.01.2025
Timing
13.01.2025 - 31.03.2025
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Online learning
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- Finnish
Seats
0 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TTV23SMTieto- ja viestintätekniikka (AMK)
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Online sessions
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
- Several online sessions during the implementation (the student can join the online session and get support from the teacher in doing the exercises)
- Distance learning (students can complete the course at their own pace, doing exercises independently)
Student workload
Distance learning 71h (exercises)
Online guidance sessions 10h
A total of 81 hours
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
18.11.2024 - 09.01.2025
Timing
13.01.2025 - 31.03.2025
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- English
Seats
0 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TIC23S1Bachelor's Degree Programme in Information and Communications Technology
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Weekly guidance for doing exercises in classrooom
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
- Weekly guidance in classroom (students can come to class to do exercises every week and get support for doing the exercises from the teacher)
- Distance learning (students can complete the course at their own pace, doing exercises independently)
Student workload
Distance learning 61h (exercises)
Guidance sessions in class 20h
A total of 81 hours
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
18.11.2024 - 09.01.2025
Timing
13.01.2025 - 31.03.2025
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- Finnish
Seats
0 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TTV23S1Tieto- ja viestintätekniikka (AMK)
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Weekly guidance for doing exercises in classrooom
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
- Weekly guidance in classroom (students can come to class to do exercises every week and get support for doing the exercises from the teacher)
- Distance learning (students can complete the course at their own pace, doing exercises independently)
Student workload
Distance learning 61h (exercises)
Guidance sessions in class 20h
A total of 81 hours
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Timing
26.08.2024 - 29.09.2024
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Online learning
Unit
School of Technology
Teaching languages
- Finnish
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
ZJA24STIAvoin AMK, tekniikka, ICT
-
ZJA24STIDA1Avoin amk, Data-analytiikka 1, Verkko
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Verkossa
Learning materials and recommended literature
Opintojakson verkkosivut (luentomateriaali, harjoitukset, nauhoitetut videot)
Teaching methods
Etäopiskelu (harjoitukset, luentomateriaaliin tutustuminen, nauhoitetut videot käytännön esimerkeistä)
Student workload
Verkkoluentomateriaaliin tutustuminen 35h (nauhoitetut luennot, joissa opettajan johdolla tehtäviä harjoitteita)
Etäopiskelu 46h (harjoitukset)
Yhteensä 81h
Further information for students
Opintojakson arviointi muodostuu palautetuista harjoituksista.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Timing
09.01.2024 - 11.02.2024
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Online learning
Unit
School of Technology
Teaching languages
- English
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
ZJA24KTIDA1Avoin amk, Data-analytiikka 1, Verkko
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Verkossa
Learning materials and recommended literature
Opintojakson verkkosivut (luentomateriaali, harjoitukset, nauhoitetut videot)
Teaching methods
Etäopiskelu (harjoitukset, luentomateriaaliin tutustuminen, nauhoitetut videot käytännön esimerkeistä)
Student workload
Verkkoluentomateriaaliin tutustuminen 35h (nauhoitetut luennot, joissa opettajan johdolla tehtäviä harjoitteita)
Etäopiskelu 46h (harjoitukset)
Yhteensä 81h
Further information for students
Opintojakson arviointi muodostuu palautetuista harjoituksista.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
20.11.2023 - 04.01.2024
Timing
08.01.2024 - 30.04.2024
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- Finnish
Seats
20 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TTV22S1Tieto- ja viestintätekniikka (AMK)
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Online lectures and, in addition, guidance in doing exercises in class
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises
Student workload
Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
20.11.2023 - 04.01.2024
Timing
08.01.2024 - 30.04.2024
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- Finnish
Seats
20 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TTV22S2Tieto- ja viestintätekniikka (AMK)
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Online lectures and, in addition, guidance in doing exercises in class
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises
Student workload
Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
20.11.2023 - 04.01.2024
Timing
08.01.2024 - 30.04.2024
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- Finnish
Seats
20 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TTV22S3Tieto- ja viestintätekniikka (AMK)
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Online lectures and, in addition, guidance in doing exercises in class
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises
Student workload
Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
20.11.2023 - 04.01.2024
Timing
08.01.2024 - 30.04.2024
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- Finnish
Seats
20 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TTV22S4Tieto- ja viestintätekniikka (AMK)
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Online lectures and, in addition, guidance in doing exercises in class
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises
Student workload
Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
20.11.2023 - 04.01.2024
Timing
08.01.2024 - 30.04.2024
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- Finnish
Seats
20 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TTV22S5Tieto- ja viestintätekniikka (AMK)
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Online lectures and, in addition, guidance in doing exercises in class
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises
Student workload
Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
20.11.2023 - 04.01.2024
Timing
08.01.2024 - 30.04.2024
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- Finnish
Seats
20 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TTV22SMTieto- ja viestintätekniikka (AMK)
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Online lectures and, in addition, guidance in doing exercises in class
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises
Student workload
Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
20.11.2023 - 04.01.2024
Timing
08.01.2024 - 30.04.2024
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- Finnish
Seats
20 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TTV22SM2Tieto- ja viestintätekniikka (AMK)
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Online lectures and, in addition, guidance in doing exercises in class
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises
Student workload
Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
20.11.2023 - 04.01.2024
Timing
08.01.2024 - 30.04.2024
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- English
Seats
20 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TIC22S1Bachelor's Degree Programme in Information and Communications Technology
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Lectures and, in addition, guidance in doing exercises in class
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
Weekly lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Weekly guidance sessions for doing the exercises
Student workload
Lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Guidance sessions in class 20h
Total 81h
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Timing
28.08.2023 - 01.10.2023
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Online learning
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- Finnish
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
ZJA23STIAvoin AMK, tekniikka, ICT
-
ZJA23STIDA1Avoin amk, Data-analytiikka 1, Verkko
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Verkossa
Learning materials and recommended literature
Opintojakson verkkosivut (luentomateriaali, harjoitukset, nauhoitetut videot)
Teaching methods
Etäopiskelu (harjoitukset, luentomateriaaliin tutustuminen, nauhoitetut videot käytännön esimerkeistä)
Student workload
Verkkoluentomateriaaliin tutustuminen 35h (nauhoitetut luennot, joissa opettajan johdolla tehtäviä harjoitteita)
Etäopiskelu 46h (harjoitukset)
Yhteensä 81h
Further information for students
Opintojakson arviointi muodostuu palautetuista harjoituksista.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Timing
09.01.2023 - 19.02.2023
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Teaching languages
- Finnish
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
ZJA23KTIDA1Avoin amk, Data-analytiikka 1, Verkko
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Verkossa
Learning materials and recommended literature
Opintojakson verkkosivut (luentomateriaali, harjoitukset, nauhoitetut videot)
Teaching methods
Etäopiskelu (harjoitukset, luentomateriaaliin tutustuminen, nauhoitetut videot käytännön esimerkeistä)
Student workload
Verkkoluentomateriaaliin tutustuminen 35h (nauhoitetut luennot, joissa opettajan johdolla tehtäviä harjoitteita)
Etäopiskelu 46h (harjoitukset)
Yhteensä 81h
Further information for students
Opintojakson arviointi muodostuu palautetuista harjoituksista.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
01.11.2022 - 05.01.2023
Timing
09.01.2023 - 28.04.2023
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- English
Seats
0 - 35
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TIC21S1Bachelor's Degree Programme in Information and Communications Technology
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
Weekly lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Student workload
Lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Total 81h
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
01.11.2022 - 05.01.2023
Timing
09.01.2023 - 28.04.2023
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Online learning
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- Finnish
Seats
0 - 210
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TTV21S3Tieto- ja viestintätekniikka (AMK)
-
TTV21S5Tieto- ja viestintätekniikka (AMK)
-
TTV21SMTieto- ja viestintätekniikka (AMK)
-
TTV21S2Tieto- ja viestintätekniikka (AMK)
-
TTV21S1Tieto- ja viestintätekniikka (AMK)
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Online
Learning materials and recommended literature
Course material page (lecture materials, exercises)
Teaching methods
Weekly online lectures (lecture material, example exercises led by a teacher)
Distance learning (exercises)
Student workload
Online lectures 35h (lectures, exercises led by a teacher)
Distance learning 46h (exercises)
Total 81h
Further information for students
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
01.08.2022 - 25.08.2022
Timing
29.08.2022 - 02.10.2022
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Teaching languages
- Finnish
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
ZJA22STIDA1Avoin amk, Data-analytiikka 1, Verkko
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Verkossa
Learning materials and recommended literature
Opintojakson verkkosivut (luentomateriaali, harjoitukset, nauhoitetut videot)
Teaching methods
Etäopiskelu (harjoitukset, luentomateriaaliin tutustuminen, nauhoitetut videot käytännön esimerkeistä)
Student workload
Verkkoluentomateriaaliin tutustuminen 35h (nauhoitetut luennot, joissa opettajan johdolla tehtäviä harjoitteita)
Etäopiskelu 46h (harjoitukset)
Yhteensä 81h
Further information for students
Opintojakson arviointi muodostuu palautetuista harjoituksista.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet
Enrollment
16.12.2021 - 09.01.2022
Timing
14.02.2022 - 31.03.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Online learning
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- Finnish
Seats
0 - 30
Degree programmes
- Bachelor's Degree Programme in Information and Communications Technology
- Bachelor's Degree Programme in Information and Communications Technology
Teachers
- Antti Häkkinen
Groups
-
TTV19SMTieto- ja viestintätekniikka
-
TTV19S1Tieto- ja viestintätekniikka
-
TTV20SMTieto- ja viestintätekniikka
-
TTV19S3Tieto- ja viestintätekniikka
-
TTV19S2Tieto- ja viestintätekniikka
-
TTV19S5Tieto- ja viestintätekniikka
-
ZJA22KTIDA1Avoin AMK, tekniikka, ICT, Data-analytiikka1
Objectives
Purpose and objectives:
The course gives you an overview of the methods of data analytics and artificial intelligence, their possibilities and applications as well as the most commonly used programming environments and libraries.
EUR-ACE Competences:
Knowledge and Understanding
Engineering Practice
Content
Definitions of data analytics and artificial intelligence
Practical applications of artificial intelligence
Examples and principles of machine learning and neural networks
Data analytics programming languages and environments: Python, R, Anaconda, Pandas
Time and location
Verkossa
Learning materials and recommended literature
Opintojakson verkkosivut (luentomateriaali, harjoitukset, nauhoitetut videot)
Teaching methods
Etäopiskelu (harjoitukset, luentomateriaaliin tutustuminen, nauhoitetut videot käytännön esimerkeistä)
Student workload
Verkkoluentomateriaaliin tutustuminen 35h (nauhoitetut luennot, joissa opettajan johdolla tehtäviä harjoitteita)
Etäopiskelu 46h (harjoitukset)
Yhteensä 81h
Further information for students
Opintojakson arviointi muodostuu palautetuista harjoituksista.
Evaluation scale
0-5
Evaluation criteria, satisfactory (1-2)
Sufficient 1: You recognize some of the most important methods, possibilities and applications of data analytics or programming environments used in them.
Satisfactory 2: You recognize some of the most important methods, possibilities and applications of data analytics and programming environments used in them.
Evaluation criteria, good (3-4)
Good 3: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them.
Very good 4: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand some principles of artificial intelligence methods.
Evaluation criteria, excellent (5)
Excellent 5: You recognize the most important methods, possibilities and applications of data analytics and artificial intelligence and the programming environments used in them. Additionally, you understand the most important principles of artificial intelligence methods.
Prerequisites
Ohjelmoinnin perusteet