We list here all the teaching activities related to our lab.
- Data Science for Business Innovation course
- Unstructured and Streaming Data Engineering
- Web and Data Science course
- Crash Course in Data Science – People@DEIB
Mooc on Data Science for Business Innovation on Coursera
We just published our new MOOC “Data Science for Business Innovation” on Coursera!
Our course is available for free on Coursera and is jointly offered by Politecnico di Milano and EIT Digital, as a compendium of the must-have expertise in data science for non-technical people, including executives, middle-managers to foster data-driven innovation.
The course is an introductory, non-technical overview of the concepts of data science. You can enrol in the course online.
The course is completely free and you can enjoy content at any time, with professional English speakers and animated, engaging materials.
The Web and Data Science course focuses on the study of large-scale socio-technical systems associated with the World Wide Web. It considers the relationship between people and technology, the ways that society and technology complement one another and the way they impact on broader society. These analyses are inherently associated with Big Data management issues.
The course is given in Como Campus by Marco Brambilla and Emanuele Della Valle.
Up-to-date calendar of the course on Google Docs: calendar
Official course page on Polimi site: web page
All the materials presented in class is published on beep: web page
|Introduction: Big Data and Data Science||Della Valle|
|Semantic Web (part 1/2): intro + RDF + SPARQL||Della Valle|
|Web Api + Scraping||Brambilla|
|Semantic Web (part 2/2): OWL + Ontology Based Data Access||Della Valle|
|NoSQL Data Models – KV, doc, column, ..||Brambilla|
|Big Data techs 1/2: MapReduce + the hadoop ecosystem + Spark||Della Valle|
|Invited seminar: AWS Serverless||Brambilla + invited|
|Big Data techs 2/2: Spark hands-on||Della Valle|
|Basic statistics in practice||Brambilla|
|PCA + clustering||Brambilla|
|Classification + Neural Networks + Deep Learning||Brambilla|
|Data science with Spark 1/2||Della Valle|
|Data science with Spark 2/2||Della Valle|
|Human Computation & Crowdsourcing||Brambilla|
|Web Information Retrieval||Brambilla|
|Mid-term project delivery||Brambilla+Della Valle|
|Final project delivery||Brambilla+Della Valle|
The exam consist in a practical part (project work) and a theoretical part (written exam with possible oral discussion).
The practical part consist in solving a realistic problem in web science / data science, based on real or realistic dataset publicly available , accessible via Web API, or provided by the teachers. 40% of the grade of this course is granted based on the evaluation of a project work.
The written exam is composed of a mix of theoretical questions regarding any of the course subjects, and excercises, regarding the technical content and how to apply it in practice.
The oral examination consists of a discussion about the written test and the practical part of the exam. It can include also questions on any subject of the course.