Course teacher(s)
John IACONO (Coordinator)ECTS credits
5
Language(s) of instruction
english
Course content
Algorithms for big data. Classical algorithm analysis and core techniques (hashing, sorting). Bloom filters, sketching, streaming, dimensionality reduction reduction, locality sensitive hashing, clustering, algorithms for external memory and cache-oblivious models.
Objectives (and/or specific learning outcomes)
Students will learn a variety of algorthmic techniques, their application and analysis.
Prerequisites and Corequisites
Required and Corequired knowledge and skills
Basic knowledge of programming in a language such as python. Basic probability theory and algebra should be well-understood.
Teaching methods and learning activities
Lectures and homework. Almost all algorithms presented will be coded fully.
Other information
Contacts
John Iacono
Campus
Plaine
Evaluation
Method(s) of evaluation
- written examination
- Project
written examination
Project
Language(s) of evaluation
- english