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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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Recommended for Data Analysis beginners

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

Kurs

Tableau'da Veri Analizi

TemelBeceri Seviyesi
4.8+
3.1K
8 saat
Gelişmiş analitik ve görselleştirme özellikleriyle Tableau becerilerinizi bir üst seviyeye taşıyın.

Program

Yardımcı Veri Analisti SQL içinde

52.7K
39 saat
Bir veritabanını sorgulamak, sonuçları analiz etmek ve SQL konusunda yetkin bir Veri Analisti olmak için ihtiyacınız olan SQL becerilerini kazanın. Önceden kodlama deneyimi gerekmez!

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Data Analysis kurs ve programlarına göz atın

Kurs

Foundations of Inference in R

Orta SeviyeBeceri Seviyesi
4.7+
507
4 saat
Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

Kurs

Bayesian Data Analysis in Python

Orta SeviyeBeceri Seviyesi
4.7+
494
4 saat
Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

Kurs

Case Study: Supply Chain Analytics in Power BI

Orta SeviyeBeceri Seviyesi
4.8+
479
4 saat
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.

Kurs

R ile Web Kazıma

Orta SeviyeBeceri Seviyesi
4.7+
479
4 saat
R kullanarak herhangi bir web sitesinden verileri verimli bir şekilde toplama ve indirmeyi öğrenin.

Kurs

RNA-Seq with Bioconductor in R

Orta SeviyeBeceri Seviyesi
4.7+
475
4 saat
Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

Kurs

Visualizations in Sigma

TemelBeceri Seviyesi
4.8+
472
2 saat
Learn to build and customize Sigma charts to tell clear, compelling data stories—no coding required.

Kurs

R'de data.table ile Veri İşleme

TemelBeceri Seviyesi
4.7+
471
4 saat
data.table kullanarak filtreleme, seçim ve grup bazında istatistik hesaplama gibi veri işlemeyle ilgili temel kavramları öğrenin.

Kurs

Dealing With Missing Data in R

TemelBeceri Seviyesi
4.7+
469
4 saat
Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

Kurs

Data Processing in Shell

Orta SeviyeBeceri Seviyesi
4.8+
465
4 saat
Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

Kurs

Python ile Spark SQL'e Giriş

İleri SeviyeBeceri Seviyesi
4.7+
464
4 saat
Pythonda SQL kullanarak Sparkta verileri nasıl işleyebileceğinizi ve makine öğrenimi özellik kümeleri oluşturabileceğinizi öğrenin.

Kurs

R'de Görselleştirme En İyi Uygulamaları

TemelBeceri Seviyesi
4.8+
463
4 saat
Yaygın grafikler, alternatif görselleştirme türleri ve algı odaklı stil geliştirmelerine genel bir bakışla verilerinizi etkili bir şekilde aktarmayı öğrenin.

Kurs

Introduction to Linear Modeling in Python

Orta SeviyeBeceri Seviyesi
4.7+
463
4 saat
Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.

Kurs

Feature Engineering with PySpark

İleri SeviyeBeceri Seviyesi
4.8+
450
4 saat
Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.

Kurs

Intermediate Importing Data in R

Orta SeviyeBeceri Seviyesi
4.8+
445
3 saat
Parse data in any format. Whether its flat files, statistical software, databases, or data right from the web.

Kurs

Experimental Design in R

Orta SeviyeBeceri Seviyesi
4.7+
434
4 saat
In this course youll learn about basic experimental design, a crucial part of any data analysis.

Kurs

Tidyverse ile Verilerle İletişim

TemelBeceri Seviyesi
4.8+
430
4 saat
Tidyverse araçlarının gücünden yararlanarak, sonuçlarınızı aktaran yayın kalitesinde grafikler ve özel stilize raporlar oluşturun.

Kurs

Foundations of Probability in Python

Orta SeviyeBeceri Seviyesi
4.8+
418
5 saat
Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

Kurs

Case Study: Analyzing Job Market Data in Tableau

TemelBeceri Seviyesi
4.7+
415
3 saat
In this case study, you’ll use visualization techniques to find out what skills are most in-demand for data scientists, data analysts, and data engineers.

Kurs

Generalized Linear Models in Python

İleri SeviyeBeceri Seviyesi
4.7+
410
5 saat
Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

Kurs

Visualizing Geospatial Data in Python

Orta SeviyeBeceri Seviyesi
4.7+
407
4 saat
Learn how to make attractive visualizations of geospatial data in Python using the geopandas package and folium maps.

Kurs

Python ile Anomali Tespiti

Orta SeviyeBeceri Seviyesi
4.8+
395
4 saat
Bu dört saatlik kursta veri analizinizdeki anormallikleri tespit edin ve Python istatistik araç setinizi genişletin.

Data Analysis ile ilgili kaynaklar

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 dk.

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 dk.

Eğitim

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 dk.

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.

    Diğer teknolojiler ve konular

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