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Machine Learning courses

Machine learning courses cover algorithms and concepts for enabling computers to learn from data and make decisions without explicit programming. Build your skills in NLP, deep learning, MLOps and more.

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Prova DataCamp for Business

Recommended for Machine Learning beginners

Build your Machine Learning skills with interactive courses, curated by real-world experts

Corso

Capire il Machine Learning

BasicLivello di competenza
4.8+
10.599 revisioni
2 h
Unintroduzione allapprendimento automatico senza bisogno di programmare.

Programma

Fondamenti di apprendimento automatico in Python

4.5+
9 revisioni
16 h
Impara larte dellapprendimento automatico e diventa un maestro nella predizione, nel riconoscimento dei modelli e negli albori dellapprendimento profondo e dellapprendimento per rinforzo.

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Corso

MLOps completamente automatizzato

IntermedioLivello di competenza
4.8+
342 revisioni
4 h
Scopri larchitettura MLOps, le tecniche CI/CD/CM/CT e i modelli di automazione per implementare sistemi ML in grado di fornire valore nel tempo.

Corso

Introduzione al versionamento dei dati con DVC

IntermedioLivello di competenza
4.7+
403 revisioni
3 h
Scopri il controllo della versione dei dati per gestire i dati ML. Configura, automatizza i flussi di lavoro e valuta i modelli senza problemi.

Corso

Modelli ARIMA in Python

AvanzatoLivello di competenza
4.8+
417 revisioni
4 h
Scopri i modelli ARIMA in Python e diventa un esperto nellanalisi delle serie temporali.

Corso

Analisi del carrello in Python

IntermedioLivello di competenza
4.8+
269 revisioni
4 h
Scopri le regole di associazione nellanalisi del paniere di mercato con Python usando i dati di una libreria e creando consigli sui film.

Corso

Unsupervised Learning in R

IntermedioLivello di competenza
4.7+
105 revisioni
4 h
Questo corso ti dà unidea di base sul clustering e sulla riduzione della dimensionalità in R dal punto di vista dellapprendimento automatico.

Corso

Machine Learning per la finanza in Python

IntermedioLivello di competenza
4.8+
213 revisioni
4 h
Modella e prevedi i valori dei dati azionari con modelli lineari, decision tree, random forest e neural network.

Corso

Supervised Learning in R: Regression

IntermedioLivello di competenza
4.6+
105 revisioni
4 h
In questo corso imparerai come prevedere cosa succederà usando la regressione lineare, i modelli additivi generalizzati, le foreste casuali e xgboost.

Corso

Metodi Ensemble in Python

AvanzatoLivello di competenza
4.8+
416 revisioni
4 h
Impara a creare modelli di machine learning avanzati ed efficaci in Python usando tecniche di ensemble come bagging, boosting e stacking.

Corso

Cluster Analysis in R

IntermedioLivello di competenza
4.8+
71 revisioni
4 h
Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

Corso

Machine Learning con caret in R

IntermedioLivello di competenza
4.8+
43 revisioni
4 h
Questo corso spiega le idee principali del machine learning, tipo come creare e valutare modelli predittivi.

Corso

Machine Learning per il marketing con Python

IntermedioLivello di competenza
4.8+
175 revisioni
4 h
From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

Corso

Machine Learning nel tidyverse

IntermedioLivello di competenza
4.8+
115 revisioni
5 h
Usa i pacchetti tidyr e purrr di tidyverse per creare, esplorare e valutare modelli di machine learning.

Corso

Modellazione con tidymodels in R

IntermedioLivello di competenza
4.8+
182 revisioni
4 h
Impara a semplificare i tuoi flussi di lavoro di machine learning con tidymodels.

Corso

Support Vector Machines in R

IntermedioLivello di competenza
4.8+
93 revisioni
4 h
Questo corso ti farà conoscere le macchine a vettori di supporto (SVM) in modo facile da capire, usando immagini e grafici.

Corso

MLOps per il business

BasicLivello di competenza
4.8+
151 revisioni
3 h
Scopri cosa sono i MLOps, inclusi gli strumenti e le pratiche che servono per automatizzare e scalare le app di machine learning.

Corso

Feature Engineering in R

IntermedioLivello di competenza
4.7+
152 revisioni
4 h
Scopri i principi della feature engineering per i modelli di machine learning e come metterli in pratica usando il framework R tidymodels.

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    Frequently asked questions

    Is machine learning easy to learn?

    DataCamp's beginner machine learning courses are a lot of hands-on fun, and they provide an excellent foundation for machine learning to advance your career or business. Within weeks, you'll be able to create models and generate predictions and insights. You'll also learn foundational knowledge of Python and R and the fundamentals of artificial intelligence.

    After that, the learning curve gets a bit steeper. Machine learning careers require a deeper understanding of statistics, math, and software engineering, all of which can be mastered at DataCamp.

    What is machine learning used for?

    In a nutshell, machine learning is a type of artificial intelligence whose algorithms, as they acquire data, produce analytical models and make predictions with little to no human intervention.

    It's difficult to find an industry that doesn't use machine learning. For example, marketers use machine learning to forecast returns on investments in marketing campaigns. Likewise, purchasing departments use machine learning to predict needed inventory.

    Businesses of all kinds use machine learning to predict customer behavior, map supply chains, and forecast revenues. Machine learning is used to predict health outcomes and to improve patient satisfaction. Machine learning helps scientists model climate change scenarios, including possible solutions.

    More specifically, machine learning is used in smart devices, search engines, and streaming services (when Netflix suggests a show or movie based on your viewing history, that's machine learning).

    What jobs can you get with machine learning skills?

    Machine learning skills are valuable in programming, data science, and other computer engineering disciplines. In addition, machine learning is a must for anyone wanting to work in robotics!

    Not all jobs that require machine learning are in tech though. For example, linguists use machine learning to track ever-changing languages and dialects. In addition, business departments, such as marketing, accounting, logistics, and purchasing, to name a few, increasingly need machine learning experts to help them make informed business decisions. Knowing machine learning can give you a step up in nearly any position, as modeling and predicting are critical business needs.

    Are machine learning skills in demand?

    Yes, machine learning skills are in high demand. According to a report by the World Economic Forum, demand for AI and ML specialists is expected to grow by 40% between 2023 and 2027.

    How much math do I need to take a machine learning course?

    If you're looking to develop a high-level understanding of machine learning concepts, you don't need much math. If you want to dive deeper and make machine learning your career (as opposed to an added value to your existing career), a foundation in statistics and algebra is helpful. If you don't have a mathematical background, that's okay. We'll teach you everything you need, and our instructors are a lot less scary than your high school calculus teacher.

    Do I need to download machine learning software to learn on DataCamp?

    You do not need to download anything while learning with DataCamp. All the tools we use are web-based.

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