Osion kuvaus

  • Databases for Data Science

    Course Description: This is an introductory course on relational databases designed for Data Science BSc students; so no prior knowledge of databases is assumed. The course covers the fundamentals of relational algebra, the design of the relational schema including the Unified Modeling Language (UML), functional dependency and normal forms, the concept of transactions, creating SQL tables (including indexes), and using SQL to query the database. 

    Following the course, the students will have the know-how to design and implement relational databases that meet the normalization rules. Moreover, the student should be able to use SQL to write and run various types of queries so as to extract the desired data from the database, an essential part when analyzing data. In particular, the course will draw on relevant examples to prepare students to apply the principles of relational databases to projects in data science.

    Note: This course is designed for Data Science BSc students; for other students we recommend taking the course CS-A1150 Tietokannat / Databases offered by Kerttu Pollari-Malmi.

    If you are a non-Data Science major and have registered for the course kindly send the instructors a brief email note with your reasons (e.g. you're following an English language major, are graduating soon, are an exchange student, etc.) for taking this Database course in particular (and not CS-A1150). We'll take all reasonable requests into consideration.

    For all the email addresses below, the domain is aalto.fi

    Instructors: Prof. Nitin Sawhney (email: nitin.sawhney@domain)

    Teaching Assistants:

    • Minh Dinh Trong (email: minh.dinhtrong@domain) - Lead TA
    • Marko Ikävalko (email: marko.ikavalko@domain)
    • Khanh Ha (email: khanh.ha@domain)
    • Hiep Nguyen (email: hiep.h.nguyen@domain)
    • Hieu Pham (email: hieu.pham@domain)
    • Linh Tran (email: linh.3.tran@domain)

    Weekly Course Schedule (detailed information can be seen here):

    Learning Sessions 

    • Tuesdays 16:15 - 18:00 (25.4.2023 - 2.6.2023)
    • 3-part sessions (approx. 30 mins each + QA) with a short break
    • Participation is mandatory

    Exercise Sessions: 

    • Wed / Thurs / Fri 10:15 - 12:00
    • Location: T5 - A133 Computer Science Building (hybrid via Zoom)
    • Hands-on sessions with applied examples and group projects
    • Participation is mandatory

    This course is project-oriented and there is no exam planned.