Advanced topics in Data Engineering & AI (5 cr)
Code: TT00CN74-3001
General information
- Enrollment
-
01.06.2024 - 09.09.2024
Registration for the implementation has ended.
- Timing
-
02.09.2024 - 15.12.2024
Implementation has ended.
- Number of ECTS credits allocated
- 5 cr
- Local portion
- 5 cr
- Mode of delivery
- Contact learning
- Unit
- Engineering and Business
- Campus
- Kupittaa Campus
- Teaching languages
- English
- Seats
- 10 - 40
- Degree programmes
- Degree Programme in Information and Communications Technology
- Degree Programme in Business Information Technology
- Degree Programme in Information and Communication Technology
- Teachers
- Mojtaba Jafaritadi
- Tommi Tuomola
- Jussi Salmi
- Teacher in charge
- Tommi Tuomola
- Groups
-
PTIETS22deaiPTIETS22 Data Engineering and Artificial Intelligence
-
PTIVIS22IData Engineering and AI
- Course
- TT00CN74
Realization has 26 reservations. Total duration of reservations is 42 h 0 min.
| Time | Topic | Location |
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Wed 04.09.2024 time 10:00 - 12:00 (2 h 0 min) |
Theory, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C3043
Teoriatila muunto
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Thu 05.09.2024 time 12:00 - 13:00 (1 h 0 min) |
Exercise, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C2027
IT telakka
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Mon 09.09.2024 time 12:00 - 14:00 (2 h 0 min) |
Theory, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_B1033
Teoriatila
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Thu 12.09.2024 time 12:00 - 13:00 (1 h 0 min) |
Exercise, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C2027
IT telakka
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Mon 16.09.2024 time 12:00 - 14:00 (2 h 0 min) |
Theory, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C1035_Delta
DELTA
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Thu 19.09.2024 time 12:00 - 13:00 (1 h 0 min) |
Exercise, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C2027
IT telakka
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Wed 25.09.2024 time 10:00 - 12:00 (2 h 0 min) |
Theory, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C3043
Teoriatila muunto
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Thu 26.09.2024 time 12:00 - 13:00 (1 h 0 min) |
Exercise, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C2027
IT telakka
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Wed 02.10.2024 time 10:00 - 12:00 (2 h 0 min) |
Theory, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C3043
Teoriatila muunto
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Thu 03.10.2024 time 12:00 - 13:00 (1 h 0 min) |
Exercise, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C2027
IT telakka
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Wed 09.10.2024 time 10:00 - 12:00 (2 h 0 min) |
Theory, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C3043
Teoriatila muunto
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Thu 10.10.2024 time 12:00 - 13:00 (1 h 0 min) |
Exercise, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C2027
IT telakka
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Wed 23.10.2024 time 10:00 - 12:00 (2 h 0 min) |
Theory, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C3043
Teoriatila muunto
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Thu 24.10.2024 time 12:00 - 13:00 (1 h 0 min) |
Exercise, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C2027
IT telakka
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Wed 30.10.2024 time 10:00 - 12:00 (2 h 0 min) |
Theory, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C3043
Teoriatila muunto
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Thu 31.10.2024 time 12:00 - 13:00 (1 h 0 min) |
Exercise, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C2027
IT telakka
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Wed 06.11.2024 time 10:00 - 12:00 (2 h 0 min) |
Theory, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C3043
Teoriatila muunto
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Thu 07.11.2024 time 12:00 - 13:00 (1 h 0 min) |
Exercise, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C2027
IT telakka
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Wed 13.11.2024 time 10:00 - 12:00 (2 h 0 min) |
Theory, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_B1033
Teoriatila
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Thu 14.11.2024 time 12:00 - 13:00 (1 h 0 min) |
Exercise, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C2027
IT telakka
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Wed 20.11.2024 time 10:00 - 12:00 (2 h 0 min) |
Theory, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C3043
Teoriatila muunto
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Thu 21.11.2024 time 12:00 - 13:00 (1 h 0 min) |
Exercise, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C2027
IT telakka
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Wed 27.11.2024 time 10:00 - 12:00 (2 h 0 min) |
Theory, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C3043
Teoriatila muunto
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Thu 28.11.2024 time 12:00 - 13:00 (1 h 0 min) |
Exercise, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C2027
IT telakka
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Wed 04.12.2024 time 09:00 - 12:00 (3 h 0 min) |
Exam, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C1027_Lambda
LAMBDA
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Wed 15.01.2025 time 09:00 - 12:00 (3 h 0 min) |
Re-exam, Advanced topics in Data Engineering & AI TT00CN74-3001 |
ICT_C2033_2034
Teoriatila muunto
|
Evaluation scale
H-5
Content scheduling
The course will be provided in two parts covering the following concepts:
Part I:
-- data security (encryption)
-- data privacy
-- data warehouses and data lakes
-- legislation on data protection (GDPR, data act)
Part II:
-- Data Regulations and Ethics in AI
-- Synthetic data generation
-- Differential privacy techniques
-- Decentralized machine learning and federated learning
Objective
After completing the course, the student can:
- work with advanced topics in data engineering and AI
Content
Advanced topics in Data Engineering, AI and data analytics such as
- application security
- data privacy
- legislation on data protection
- ethics of AI
Materials
Course materials are prepared by the lecturer from various sources including books, online material, etc.
Recommended books to study in this course are:
-- Practical Data Privacy: Enhancing Privacy and Security in Data 1st Edition by Katharine Jarmul
-- Fundamentals of Data Engineering: Plan and Build Robust Data Systems 1st Edition
by Joe Reis and Matt Housley
Teaching methods
Weekly contact sessions with total of 3 hours of theory and practical exercises.
Exam schedules
Exams including retake will be in Week 48 or 49 (at the same day as we have the regular lectures).
International connections
The course includes about 11 theory sessions and personal practice tasks.
This learning method combines theoretical knowledge with practical applications and real-world examples. It emphasizes understanding data engineering fundamental and privacy AI concepts, studying relevant technologies and techniques, and exploring practical implementations and use cases. Hands-on exercises, case studies, and projects will be incorporated to reinforce the learning experience
Completion alternatives
The exercises are mainly performed using Jupyter Notebook or other types of code scripts. Students will use TensorFlow and/or PyTorch. Strong python programming skills are needed to complete the exercises in part II.
Student workload
11 sessions (2.9-29.11.24 ) each 3 hours (2h lecture, 1h practice)+ Exam
Contact hours:
- Weeks 36 - 47: Theory & practice (3h/week): 11 x 3h = 33h
- Week 48: Exam: 2h
- In addition, about 5 support and inquiry hours (biweekly): 5x 1h = 5h
Total contact hours: 40 hours
Independent study and homework: about 90 h