Advanced practical studiesLaajuus (3 cr)

Objective

This course introduces participants to the application of selected tools for data analytics, artificial intelligence (AI), and machine learning (ML). Participants are required to have prior knowledge of cloud services, data analytics, and AI (through previous program modules or equivalent knowledge). Basic programming skills (Python) and familiarity with SQL are highly recommended. The course content is designed for software developers or professionals in similar advanced ICT roles, as well as recent graduates with a bachelor-level degree in the field.

Knowledge:
• Gain a deeper understanding of the key principles of data storage, data analytics, and machine learning, as well as their significance in modern software development.
Skills:
• Be able to independently apply data analytics tools and methods for data collection, preprocessing, analysis, and visualization using selected tools.
• Be able to apply simple machine learning models.
Responsibility and Independence:
• Understand the ethical and societal impacts of data analytics and artificial intelligence and be able to account for them in professional work.

Content

• Overview of orgestration tools for data-analysis and data science
• Implementing a data Warehouse
• Implementing a Lakehouse
• Implementing real-time intelligence
• Implementing a data science and machine learning solutions
• Case example: Company Microsoft