Advanced topics in Data Engineering & AI (5 op)

Arviointiasteikko

H-5

Sisällön jaksotus

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

Tavoitteet

After completing the course, the student can:
- work with advanced topics in data engineering and AI

Sisältö

Advanced topics in Data Engineering, AI and data analytics such as
- application security
- data privacy
- legislation on data protection
- ethics of AI

Oppimateriaalit

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

Opetusmenetelmät

Weekly contact sessions with total of 3 hours of theory and practical exercises.

Tenttien ajankohdat ja uusintamahdollisuudet

Exams including retake will be in Week 48 or 49 (at the same day as we have the regular lectures).

Kansainvälisyys

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

Toteutuksen valinnaiset suoritustavat

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.

Opiskelijan ajankäyttö ja kuormitus

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