Rajaa hakua
Piilota rajaukset
TE00CN56-3003
Opiskelija tarvitsee oman tietokoneen, jolla voi ajaa intel-arkkitehtuurin virtuaalikoneita. Lisäksi on suositeltavaa hankkia oma USB-ethernet adapteri jos koneessa ei ole kiinteää ethernet-liitäntää.
Materiaalien jako ja kurssin muu tiedottaminen tapahtuu Itslearning-alustan kautta.
TE00CR36-3002
Course material and information shared through itslearning.
TE00CX51-3001
This course is for anyone with an interest in starting a podcast. It is practical with a strong emphasis on learning by doing. By the end of the course each group will have a fully defined podcast concept, a clear brand outline, a marketing roadmap and one ready to publish podcast episode in the bag. Although the language of instruction is English your podcast can be recorded in your language of preference.
TE00CS06-3003
Opintojaksolle osallistuvalta edellytetään äidinkielen tasoista suomen kielen taitoa eli C-taitotasoa.
Opiskelijalla on vastuu tarkistaa edeltävyysehtojen täyttyminen ennen ilmoittautumista.
Opettajalla on peruste hylätä ilmoittautuminen, jos edeltävyysehdot eivät täyty.
Viestintäkanavana käytetään sähköpostia ja Itslearningia.
TE00CM20-3003
The teacher will inform about the course practicalities in itslearning.
If you have any questions about the course, please contact the course teachers by email.
Enroll to course in Peppi. When your enrollment is accepted, you'll get access to course's itslearning (within a day or two after enrollment acceptance).
TT00CD87-3002
Course material and assignments in Its Learning and AWS academy.
TT00CN68-3003
Qualifications:
Before taking an "Introduction to Data Engineering with Python" course, students typically need a foundational understanding of several key areas. Here are the mandatory and recommended prerequisite courses and topics.
1. Mandatory Prerequisites:
1.1. Programming:
1.1.1. Introduction to Programming: Knowledge of programming fundamentals,
including concepts like variables, loops, conditionals, and functions.
1.1.2. Python Programming: Familiarity with Python, including basic syntax, data
types, control structures, and function and modules
1.1.3. Error Handling
1.1.4. Object-oriented programming (OOP)
1.1.5. Data Manipulation: Skills in using Pandas library including DataFrames and
Series, reading, writing, filtering, and transforming data
1.2. Databases: Knowledge of how databases work, including concepts like tables, keys, normalization, and indexing.
2. Recommended Topics:
2.1. Algorithms and Data Structures: Basic understanding of algorithms and data
structures such as arrays, lists, trees, and graphs, which are crucial for data
processing
2.2. Having the fundamental knowledge of cloud services or passing the Cloud Services
Course in TUAS (Lecturer: Ali Khan)
2.3. Version Control Systems: Basic understanding of tools like Git for version control.
2.4. Basic Algebra and Calculus: Fundamental math skills to handle data transformations
and calculations.
2.5. Statistics: Understanding of basic statistical concepts like mean, median, standard
deviation, and probability distributions.+
TE00BR86-3004
** Prerequisites for Back- End Development Course:
1- JavaScript: Basic Syntax and Control Structures, Functions and Scope, Asynchronous Programming
2- Databases
** Recommendations (Optional but Beneficial):
1- Basic Understanding of RESTful APIs: Knowledge of HTTP methods (GET, POST, PUT, DELETE) and status codes.
2- Experience with JSON: Understanding of JSON format for data interchange.
3- Basic Knowledge of Git: Familiarity with version control using Git.
TE00BR84-3004
An oral communication is used during the classes. For the written communication Itslearning and e-mail are applied.
TE00CS06-3002
Opintojaksolle osallistuvalta edellytetään äidinkielen tasoista suomen kielen taitoa eli C-taitotasoa.
Opiskelijalla on vastuu tarkistaa edeltävyysehtojen täyttyminen ennen ilmoittautumista.
Opettajalla on peruste hylätä ilmoittautuminen, jos edeltävyysehdot eivät täyty.
Viestintäkanavana käytetään sähköpostia ja Itslearningia.
TE00CS06-3001
Opintojaksolle osallistuvalta edellytetään äidinkielen tasoista suomen kielen taitoa eli C-taitotasoa.
Opiskelijalla on vastuu tarkistaa edeltävyysehtojen täyttyminen ennen ilmoittautumista.
Opettajalla on peruste hylätä ilmoittautuminen, jos edeltävyysehdot eivät täyty.
Viestintäkanavana käytetään sähköpostia ja Itslearningia.
TE00BR81-3005
the course's and theFIRMA itslearning and Microsoft Teams
3011632-3006
Kurssin opetusympäristö infoineen ja materiaaleineen on itsLearning.
Kurssilla käytetään myös muita sovelluksia kuten Odoo ja SAP.
Opetus toteutetaan paikan päällä kampuksella. Käytännön ERP harjoitukset (SAP ja Odoo) edellyttävät läsnäoloa luokassa. Harjoitustyö tehdään pienryhmässä ja edellyttää läsnäoloa tunnilla.
TT00CN73-3001
Course material and assignments in Its Learning and AWS academy.
TT00CN68-3004
Qualifications:
Before taking an "Introduction to Data Engineering with Python" course, students typically need a foundational understanding of several key areas. Here are the mandatory and recommended prerequisite courses and topics.
1. Mandatory Prerequisites:
1.1. Programming:
1.1.1. Introduction to Programming: Knowledge of programming fundamentals,
including concepts like variables, loops, conditionals, and functions.
1.1.2. Python Programming: Familiarity with Python, including basic syntax, data
types, control structures, and function and modules
1.1.3. Error Handling
1.1.4. Object-oriented programming (OOP)
1.1.5. Data Manipulation: Skills in using Pandas library including DataFrames and
Series, reading, writing, filtering, and transforming data
1.2. Databases: Knowledge of how databases work, including concepts like tables, keys, normalization, and indexing.
2. Recommended Topics:
2.1. Algorithms and Data Structures: Basic understanding of algorithms and data
structures such as arrays, lists, trees, and graphs, which are crucial for data
processing
2.2. Having the fundamental knowledge of cloud services or passing the Cloud Services
Course in TUAS (Lecturer: Ali Khan)
2.3. Version Control Systems: Basic understanding of tools like Git for version control.
2.4. Basic Algebra and Calculus: Fundamental math skills to handle data transformations
and calculations.
2.5. Statistics: Understanding of basic statistical concepts like mean, median, standard
deviation, and probability distributions.