Università di Napoli Federico II
Data Science con Python e R Specialization
Università di Napoli Federico II

Data Science con Python e R Specialization

Diventa un esperto dei dati con Python e R. Crea le basi per la tua carriera da Data Scientist. Esegui analisi su data set reali e impara ad utilizzare correttamente R e Python

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Get in-depth knowledge of a subject

(37 reviews)

Intermediate level

Recommended experience

Flexible schedule
2 months at 10 hours a week
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject

(37 reviews)

Intermediate level

Recommended experience

Flexible schedule
2 months at 10 hours a week
Earn a career credential
Share your expertise with employers

Overview

  • Apprenderai le basi per realizzare un programma in Python e riconoscere i principali comandi

  • Conoscere ed utilizzare le principali istruzioni e strutture dati in R nei tipici metodi di apprendimento supervisionato e non supervisionato

  • Conoscere le architetture di reti neurali artificiali, sia shallow che deep

  • Utilizzare le reti neurali artificiali per la classificazione, segmentazione e object detection

What’s included

Shareable certificate

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Taught in Italian
26 practice exercises

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Università di Napoli Federico II

Specialization - 3 course series

What you'll learn

  • Impara i  Principi base della Programmazione in Python, i Linguaggi Interpretati e gli Ambienti di Sviluppo

  • Impara a conoscere la  programmazione orientata agli oggetti e i costrutti più utilizzati: classi, oggetti, ereditarietà multipla

  • Utilizza in modo appropriato i Moduli e Package. Impara come gestire i Files ed eccezioni e come accedere a Data Base

Skills you'll gain

Category: Python Programming
Category: Object Oriented Programming (OOP)
Category: File Management
Category: Scripting
Category: Database Management
Category: Computer Programming
Category: Debugging
Category: Programming Principles
Category: Databases
Category: Scripting Languages

What you'll learn

  • Importare, manipolare e visualizzare dati mediante R e i pacchetti inclusi in tidyverse come dplyr e ggplot2

  • Riconoscere e risolvere in R, mediante i pacchetti aggiuntivi leaps, glmnet, pls, problemi di apprendimento supervisionato e non supervisionato

  • Comprendere le differenze tra reti neurali artificiali di tipo shallow e deep

Skills you'll gain

Category: R Programming
Category: Ggplot2
Category: Data Manipulation
Category: Regression Analysis
Category: Supervised Learning
Category: Dimensionality Reduction
Category: Unsupervised Learning
Category: Predictive Modeling
Category: Deep Learning
Category: Artificial Neural Networks
Category: Data Wrangling
Category: Data Analysis
Category: Data Structures
Category: Tidyverse (R Package)
Category: Data Mining
Category: Machine Learning
Category: Exploratory Data Analysis
Category: Statistical Analysis

What you'll learn

  • Imparare a manipolare e visualizzare i dati python, tramite l'uso di alcune librerie molto diffuse

  • Imparare a instanziare, addestrare ed utilizzare reti neurali (feedforward e ricorrenti) usando scikit learn

  • Imparare ad usare i tool Keras e PyTorch per il deep learning

  • Instanziare e utilizzare una rete encoder/decoder per la segmentazione semantica e come usare reti deep pre-addestrate per la object detection

Skills you'll gain

Category: Pandas (Python Package)
Category: NumPy
Category: Scikit Learn (Machine Learning Library)
Category: PyTorch (Machine Learning Library)
Category: Matplotlib
Category: Computer Vision
Category: Data Manipulation
Category: Image Analysis
Category: Python Programming
Category: Applied Machine Learning
Category: Deep Learning
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Artificial Neural Networks
Category: Keras (Neural Network Library)

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Instructors

Carlo Sansone
Università di Napoli Federico II
2 Courses1,228 learners
Flora Amato
Università di Napoli Federico II
1 Course1,849 learners

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