Opetussuunnitelmat

Opetussuunnitelma

Osaamisalueet

Arviointikehikko

Tietoa koulutuksesta

Description

KA00DL07	Data Engineering (5 cr)
Prerequisites	Not applicable
Objectives	The student can estimate different data storage and processing solutions in terms of data type, volume, overall needs, and costs. The student knows basics of databases. The student has basic knowledge about cloud-based data processing tools and programming languages. The student understands the levels of data processing and data products. The student can perform data cleaning and categorization. The student can use cloud-based systems and services to store, process, and access data.
Content	- Programming languages and software libraries for data engineering - Data sources and storage solutions - Cleaning and categorizing data - Cloud-based systems and solutions for data analysis
Recommended optional programme components	If necessary, the student advisor will recommend optional programme components for each student based on their individual study plan.
Accomplishment methods	Not applicable
Execution methods	Not applicable
Materials	Not applicable
Literature	Not applicable
Evaluation Criteria	0-5
Evaluation Criteria	satisfactory (1-2) I understand how data engineering works, why it is needed and what are the essential software and storage components. I am familiar with the different data types and data products and the steps of data processing. I can maintain and improve local and cloud-based data engineering tools. good (3-4) I can create and maintain small-scale data warehouse using software and cloud storage tools. I can estimate the cost and risks of different data engineering solutions. excellent (5) I can plan the architecture and implementation of complicated data warehouse. I can construct most of the data warehouse components and understand how all of them work. I can estimate the financial and security aspects of data warehouse solutions and select the optimal choice.
Assessment Frameworks	Assessment framework
Further Information	Not applicable
Responsible persons	Not applicable
Links	Assessment framework

Implementations

Show old implementations

• 30.10.2023 - 20.12.2023 (KA00DL07-3002 | VAI23S24K, DPD23SYTIK, DPD23SYTEKN, EXN23S24KDDMDAPMHNU, DPM23KYTIK)
Group(s)
VAI23S24K, DPD23SYTIK, DPD23SYTEKN, EXN23S24KDDMDAPMHNU, DPM23KYTIK

Max Seats
Not applicable

Evaluation Criteria
0-5

Language of Instruction
English

Type of Course
Avoin amk, Information Technology, Studies in English, Master, Data Analysis, Databases

Responsible Teacher
Ilpo Virtanen

Mode of Delivery
R&D Studies: 0.00 cr
Virtual Studies: 5.00 cr
Contact Teaching: 0 cr

Teacher(s)
Ilpo Virtanen

Smaller Group(s)
Tutkinto-opiskelijat, Avoin amk

Evaluation Criteria
0-5

Assessment Methods and Criteria
Not applicable

Planned Learning Activities and Teaching Methods
Online teaching

Location and time
Check from calendar

Learning environments


Recommended or Required Reading
Material in Moodle

Further Information
Not applicable

Completion Alternatives
Not applicable

Teacher(s)
Ilpo Virtanen

Work Placement and Working Life Connections
Not applicable

Exam Schedule
Not applicable

International Connections
Not applicable

Student's Time Use and Workload
135 hours of work, 32h of teaching, 103h of independent work

Learning Progress
Online lectures 4h per week

Evaluation criteria accepted
1-2: 50% - 70% of points
3-4: 70% - 90% of points
5: Over 90% of points


Evaluation criteria failed
Less than 50% of total points