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.
Enrollment
20.11.2023 - 04.01.2024
Timing
08.01.2024 - 30.04.2024
Number of ECTS credits allocated
3 op
Mode of delivery
Contact teaching
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)
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
Location and time
Online lectures and, in addition, guidance in doing exercises in class
Materials
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
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
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.
Qualifications
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
Contact teaching
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)
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
Location and time
Online lectures and, in addition, guidance in doing exercises in class
Materials
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
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
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.
Qualifications
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
Contact teaching
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)
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
Location and time
Online lectures and, in addition, guidance in doing exercises in class
Materials
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
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
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.
Qualifications
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
Contact teaching
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)
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
Location and time
Online lectures and, in addition, guidance in doing exercises in class
Materials
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
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
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.
Qualifications
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
Contact teaching
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)
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
Location and time
Online lectures and, in addition, guidance in doing exercises in class
Materials
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
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
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.
Qualifications
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
Contact teaching
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)
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
Location and time
Online lectures and, in addition, guidance in doing exercises in class
Materials
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
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
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.
Qualifications
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
Contact teaching
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)
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
Location and time
Online lectures and, in addition, guidance in doing exercises in class
Materials
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
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
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.
Qualifications
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
Contact teaching
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
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
Location and time
Lectures and, in addition, guidance in doing exercises in class
Materials
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
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
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.
Qualifications
Ohjelmoinnin perusteet
Timing
28.08.2023 - 01.10.2023
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance 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
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
Location and time
Verkossa
Materials
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
Opintojakson arviointi muodostuu palautetuista harjoituksista.
Evaluation scale
0-5
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.
Qualifications
Ohjelmoinnin perusteet
Timing
09.01.2023 - 19.02.2023
Number of ECTS credits allocated
3 op
Mode of delivery
Contact teaching
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
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
Location and time
Verkossa
Materials
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
Opintojakson arviointi muodostuu palautetuista harjoituksista.
Evaluation scale
0-5
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.
Qualifications
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
Contact teaching
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
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
Materials
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
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
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.
Qualifications
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
Distance 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)
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
Location and time
Online
Materials
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
The assessment of the course consists of returned exercises.
Evaluation scale
0-5
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.
Qualifications
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
Contact teaching
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
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
Location and time
Verkossa
Materials
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
Opintojakson arviointi muodostuu palautetuista harjoituksista.
Evaluation scale
0-5
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.
Qualifications
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
Distance 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
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
Location and time
Verkossa
Materials
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
Opintojakson arviointi muodostuu palautetuista harjoituksista.
Evaluation scale
0-5
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.
Qualifications
Ohjelmoinnin perusteet