The rapid proliferation of the Internet and related services, especially social networks and user-generated content, has resulted in incredible amounts of digital information. This is better known as "Big Data" and enables new ways of marketing. However, analyzing massive amounts of data requires specialized tools and methods. Industry managers and researchers increasingly turn to technological innovations that make decision-making effective in Big Data.

The course covers three topics. Each of the three topics is covered in a separate block. Your progress will be assessed through theoretical and practical assignments you can complete at home. 

You must attend at least 80% of all class sessions to pass the course (whether online or physical). In the case of online sessions, we expect active participation and a camera turned on. Students are allowed to miss a total of two sessions. Missing one session will not require additional direction; on the second missed session or more, written completion of a replacement assignment will be required. In the case of technical difficulties, evidence of the technical problem (e.g., screenshots) is required.

Grading is based on the following components: Practical (practical assignments), theoretical assignments (theoretical assignments), and in-class participation.

Practical Assignments: practical assignments must be completed for each block. For example, students must complete small assignments. This part is to demonstrate the practical skills learned in this course.

Theoretical Assignments: For each block, students have to answer theoretical questions.

These grading components are added together to calculate the final grade, which is based on the following grading scheme:

To successfully pass this course, your cumulative points must exceed 60 points.