Piano di Studio Informatica Applicata (Machine Learning e Big Data)

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Nuovo Manifesto degli Studi del Corso di Laurea Magistrale in

Informatica Applicata (Machine Learning e Big Data) - LM-18 

per gli studenti immatricolati a partire dall'A.A. 2018-2019

per accedere al piano di studio in versione pdf, cliccare qui

 

 

First year

I SEMESTER

 

Scientific Computing (part I - Data science and simulation)*

6 CFU-ETCS - MAT/08

Physics and Quantum Computing

6 CFU-ETCS  - FIS/05

Machine Learning (part I - Statistical machine learning and neural networks)**

6 CFU-ETCS  - INF/01

Machine Learning (part II - Deep learning)** 6 CFU-ETCS  - INF/01
   

II SEMESTER

 

Scientific Computing (part II - Geometrical mappings and transforms)* 

6 CFU-ETCS - MAT/08

Intelligent Signal Processing

6 CFU-ETCS  - INF/01

Computer Graphics: Animation and Simulation

6 CFU-ETCS - INF/01

Data Science Technology

6 CFU-ETCS - INF/01

*, ** joint exams  
 

Second year

I SEMESTER  
Internet of Things and IoT Lab (part I - Sensor networks ) ***

6 CFU-ETCS  - INF/01

Multimodal Machine Learning

6 CFU-ETCS  - INF/01

High Performance Computing 6 CFU-ETCS - MAT/08
Elective 6 CFU-ETCS
   
II SEMESTER  
Internet of Things and IoT Lab (part II - Architecture and Systems) *** 6 CFU-ETCS - INF/01
Cloud Computing 6 CFU-ETCS - INF/01
Elective 6 CFU-ETCS

 

*** joint exam

Electives

Cyber Security °°

6 CFU-ETCS  - INF/01

Semantic Artificial Intelligence °°

6 CFU-ETCS  - INF/01

Computer Vision °

6 CFU-ETCS  - INF/01

Information and Knowledge Management °°

6 CFU-ETCS - INF/01

Big Geo-Data Management °

6 CFU-ETCS - GEO/04

IOS Programming °°°

6 CFU-ECTS - INF/01

   

° First Semester; °° Second Semester;

 
°°° Only for students of the iOS Foundation Program Apple - UniParthenope  
   
Stage/Internship 6 CFU-ETCS
Language certifications  3 CFU-ETCS 
MSc Thesis 21 CFU-ETCS