Big Data Lab
Professor: Fabrizio Iozzi
Data became “big” when it started coming from everywhere: cell phones, social media, installed or remote sensors, cameras, microphones and many more devices. The volumes of data are large and growing on a daily basis. Data volumes, variety and velocity are inundating companies that are not always able to cope with them due to a lack of instruments, skills or motivation.
Big data can be analyzed to understand and predict the complex “behaviors” of single individuals or of large societies, of single devices and of complex factories, of natural events.
Analysts deal with big data by using specially designed tools and algorithms. The major difference from traditional data analytics is that little or no assumption is made before the analysis starts: we approach big data with our minds free from any expectation of what we might discover.
During this course you will be introduced to some approaches of dealing with big data, in particular with machine learning algorithms. We will look together and will try to understand real sets of data, in class and in small groups. The classes will be mostly interactive with intensive use of computers. On Wednesday afternoon we will visit a big player in the computer science industry and have a chance to talk to the company management.
Prerequisites: Students are expected to have basic knowledge in analytical plane geometry and some high school algebra. The course is highly interactive and we expect students to be genuinely interested in experimenting with the techniques learnt with a computer. Students are asked to bring their own laptops (not tablets).
Assessment: Friendly qualitative feedback will be given based on individual class participation and final presentations by small groups.
The course is an introduction to our university’s interactive and hands-on approach to teaching the Bachelor of Science in Economics, Management and Computer Science.