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Data Analysis courses

Data analysis courses teach techniques for inspecting, cleaning, transforming, and modeling data to discover useful information, inform conclusions, and support decision-making. Build your analysis skills using technologies such as Python, R and SQL.

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Prova DataCamp for Business

Recommended for Data Analysis beginners

Build your Data Analysis skills with interactive courses, curated by real-world experts

Corso

Analizzare i dati in Tableau

BasicLivello di competenza
4.8+
3.1K
8 ore
Migliora le tue competenze con Tableau grazie ad analisi e visualizzazioni avanzate.

Programma

Analista dati associato in SQL

51.9K
39 ore
Acquisisci le competenze SQL necessarie per interrogare un database, analizzare i risultati e diventare un analista di dati esperto di SQL. Non è richiesta alcuna esperienza di codifica!

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Sfoglia i corsi e programmi su Data Analysis

Corso

Fondamenti di inferenza in R

IntermedioLivello di competenza
4.7+
501
4 ore
Impara a tirare conclusioni su una popolazione partendo da un campione di dati usando un processo chiamato inferenza statistica.

Corso

Visualizations in Sigma

BasicLivello di competenza
4.8+
482
2 ore
Learn to build and customize Sigma charts to tell clear, compelling data stories—no coding required.

Corso

Web scraping in R

IntermedioLivello di competenza
4.7+
480
4 ore
Scopri come raccogliere e scaricare dati da qualsiasi sito web in modo efficiente usando R.

Corso

Case Study: Supply Chain Analytics in Power BI

BasicLivello di competenza
4.8+
475
4 ore
Learn how to use Power BI for supply chain analytics in this case study. Create a make vs. buy analysis tool, calculate costs, and analyze production volumes.

Corso

RNA-Seq with Bioconductor in R

IntermedioLivello di competenza
4.7+
475
4 ore
Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

Corso

Dealing With Missing Data in R

BasicLivello di competenza
4.7+
472
4 ore
Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

Corso

Manipolazione dei dati con data.table in R

BasicLivello di competenza
4.7+
472
4 ore
Impara i concetti fondamentali sulla manipolazione dei dati, come filtrare, selezionare e calcolare statistiche di gruppo usando data.table.

Corso

Data Processing in Shell

IntermedioLivello di competenza
4.8+
463
4 ore
Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

Corso

Buone pratiche di visualizzazione in R

BasicLivello di competenza
4.8+
458
4 ore
Learn to effectively convey your data with an overview of common charts, alternative visualization types, and perception-driven style enhancements.

Corso

Introduzione a Spark SQL in Python

AvanzatoLivello di competenza
4.7+
458
4 ore
Impara a gestire i dati e a creare set di funzionalità di machine learning in Spark usando SQL in Python.

Corso

Introduzione alla modellazione lineare in Python

IntermedioLivello di competenza
4.7+
458
4 ore
Scopri i concetti e le applicazioni dei modelli lineari con Python e crea modelli per descrivere, prevedere ed estrarre informazioni dai modelli di dati.

Corso

Feature Engineering with PySpark

AvanzatoLivello di competenza
4.8+
454
4 ore
Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.

Corso

Intermediate Importing Data in R

IntermedioLivello di competenza
4.8+
444
3 ore
Parse data in any format. Whether its flat files, statistical software, databases, or data right from the web.

Corso

Visualizzare le serie temporali in R

IntermedioLivello di competenza
4.8+
436
4 ore
Impara a visualizzare le serie temporali in R, poi fai pratica con un caso di studio sulla selezione dei titoli azionari.

Corso

Comunicare con i dati nel Tidyverse

BasicLivello di competenza
4.8+
430
4 ore
Sfrutta la potenza degli strumenti tidyverse per creare grafici di qualità professionale e report personalizzati che comunichino i tuoi risultati.

Corso

Progettazione Sperimentale in R

IntermedioLivello di competenza
4.7+
428
4 ore
In questo corso imparerai le basi della progettazione sperimentale, una parte fondamentale di qualsiasi analisi dei dati.

Corso

Foundations of Probability in Python

IntermedioLivello di competenza
4.8+
419
5 ore
Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

Corso

Modelli lineari generalizzati in Python

AvanzatoLivello di competenza
4.7+
410
5 ore
Aggiungi i modelli logistico e di Poisson al tuo set di strumenti di regressione e impara a usarli, capirli e verificarli, oltre che a fare previsioni.

Corso

Visualizing Geospatial Data in Python

IntermedioLivello di competenza
4.7+
406
4 ore
Learn how to make attractive visualizations of geospatial data in Python using the geopandas package and folium maps.

Corso

Rilevamento delle anomalie in Python

IntermedioLivello di competenza
4.8+
394
4 ore
Scopri le anomalie nellanalisi dei tuoi dati e dai una spinta al tuo kit di strumenti statistici Python in questo corso di quattro ore.

Risorse correlate su Data Analysis

blog

How to Become a Data Analyst in 2026: 5 Steps to Start Your Career

Learn how to become a data analyst and discover everything you need to know about launching your career, including the skills you need and how to learn them.
Elena Kosourova's photo

Elena Kosourova

15 min

blog

30 Data Analytics Projects for All Levels in 2026

Explore our list of data analytics projects for beginners, final-year students, and professionals. The list consists of guided/unguided projects and tutorials with source code.
Abid Ali Awan's photo

Abid Ali Awan

13 min

Tutorial

Alteryx Tutorial: A Comprehensive Hands-On Guide for Data Analytics

Dive into our detailed Alteryx tutorial and learn how this powerful data analytics tool can transform your data handling experience. This guide covers everything from installation to advanced workflow automation in Alteryx, making it the perfect resource for beginners and seasoned data professionals alike.
Kurtis Pykes 's photo

Kurtis Pykes

11 min

Ready to apply your skills?

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    Frequently asked questions

    Is data analysis easy to learn?

    It’s different for everyone. Some people pick up data analysis very quickly, while others need a bit more time. The underlying theory and concepts are not hard to understand (or highly technical), but you’ll need to learn a few popular data analysis tools. 

    This includes SQL and databases, a programming language such as Python or R, spreadsheets and Excel, and software such as Power BI or Tableau. 

    It might sound like a lot, but each technology is easy to learn individually, especially when you choose data analysis courses from a dedicated online training provider like DataCamp.

    Has AI changed the role or need for data analysts?

    AI is indeed transforming the data analyst's role. Rather than replacing them, it has automated repetitive tasks, freeing analysts to focus on complex issues, interpret AI results, and strategize. Although AI aids in data analysis, human supervision for training and adjusting AI models remains crucial. Thus, AI is changing the analyst role but increased its importance.

    Which data analysis course is the best?

    We only release courses that meet our high quality standards, which is why DataCamp is known as a leading platform for learning data analysis! That being said, our Data Analyst with Python Career Track is one of our most popular, comprehensive course programs for acquiring the skills to become a data analyst from scratch.

    How can I become a data analyst quickly?

    To become a data analyst quickly, a structured learning path like DataCamp's Career Tracks is beneficial. For example, programs such as our Data Analyst with Python and Data Analyst with Power BI Tracks are designed to gradually upskill you in the various concepts, technologies and processes required to be a data analyst.

    And importantly, becoming a data analyst requires dedication and consistency in learning, while embracing a positive attitude towards problem-solving. Applying your knowledge to real-world projects helps solidify concepts, and creating a data portfolio to showcase these projects can demonstrate your proficiency to potential employers.

    See our 'How to become a data analyst' article for further guidance.

    How can online courses help you learn data analytics?

    DataCamp's courses provide a flexible and convenient way to learn data analytics at your own pace. Our data analytics courses, taught by industry experts, offer interactive exercises and practical projects that help you apply theoretical concepts to real-world scenarios.

    Do I need a background in programming to start learning data analytics?

    No, you don't need a programming background to start learning data analytics. Our beginner courses, such as Introduction to SQL and Analyzing Data in Tableau, are designed to accommodate beginners and gradually introduce programming concepts, if needed.

    What jobs can you get with data analysis skills?

    With data analysis skills in your technical tool kit, you have plenty of job options:

    • Data analyst
    • Database administrator
    • Systems analyst
    • Business intelligence
    • Digital marketer
    • Data scientist
    • Financial analyst
    • And many more!

    Because the modern business world is data-driven, people with data analysis skills find it easy to get work in an eclectic mix of industries and sectors.

    Are data analysis skills in demand?

    Yes, data analysts are some of the most in-demand professionals worldwide. Data from the US Bureau of Labor Statistics suggest the number of jobs for analysts is expected to grow by 23% between 2021 and 2031.

    How can I prove my data analysis skills to employers?

    To prove your data analysis skills to employers, you can complete our industry recognized Data Analyst Certification. This certification showcases your data analysis knowledge using SQL and either Python or R.

    What tools and software are commonly used in data analytics?

    Common tools in data analytics include Excel, SQL, Python, R, Tableau, and Power BI. These tools help in data manipulation, analysis, and visualization.

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