Coursera

Ferramentas para Ciência de Dados: Introdução ao R (Coursera)

Offered by FIA Business School,
Ferramentas para Ciência de Dados: Introdução ao R (Coursera)

Nossas boas-vindas ao Curso Ferramentas para Ciência de Dados: Introdução ao R. Neste curso, você aprenderá que o mundo evoluiu muito quando o assunto é tomada de decisão baseada em dados e já não é possível comparar a quantidade de informações a que temos acesso atualmente com o que tínhamos disponíveis décadas atrás.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Basicamente, a ciência de dados tem como objetivo encontrar formas inovadoras para analisar e impulsionar o crescimento de negócios, por isso, muitas ferramentas analíticas foram adotadas pelo mercado e são utilizadas para processar os dados, realizar análises avançadas e facilitar o processo de tomada de decisão.
Ao final deste curso, você será capaz de conhecer as principais ferramentas de mercado e aprender os fundamentos da linguagem R e como utilizá-la em seu dia-a-dia. O curso cobre a os principais tópicos:

  • Ferramentas para Data Science;
  • Introdução à linguagem de programação em R;
  • Utilização de ambiente de desenvolvimento;
  • Instalação e utilização de bibliotecas no R;
  • Escrita de funções em R;
  • Escrita, leitura e manipulação de dados;
  • Análises gráficas.

This course can be applied to multiple Specializations or Professional Certificates programs. Completing this course will count towards your learning in any of the following programs:

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

AI for Efficient Programming: Harnessing the Power of LLMs (Coursera) Coursera
Fred Hutchinson Cancer Center

AI for Efficient Programming: Harnessing the Power of LLMs (Coursera)

Robotics & Computer Vision

This course on Artificial Intelligence (AI) for software development explores the use of AI large language models such as ChatGPT, Bard, and others and their potential benefits and challenges. Through examples and hands-on activities, you will develop an understanding of the ways in which AI can speed up software development tasks and free up time for more creative and strategic work.

Aug 10th 2026
4 Weeks
Artificial Intelligence Coding Data Science
Details
Population Health: Responsible Data Analysis (Coursera) Coursera
Leiden University

Population Health: Responsible Data Analysis (Coursera)

Statistics & Data Analysis Data Science

In most areas of health, data is being used to make important decisions. As a health population manager, you will have the opportunity to use data to answer interesting questions. In this course, we will discuss data analysis from a responsible perspective, which will help you to extract useful information from data and enlarge your knowledge about specific aspects of interest of the population.

Aug 10th 2026
4 Weeks
Data Analysis R Programming Regression Analysis
Details
Redes Ecológicas (Coursera) Coursera
Universidade de São Paulo, Brasil

Redes Ecológicas (Coursera)

Statistics & Data Analysis Data Science

Todos os seres vivos estão conectados entre si por interações ecológicas, formando a “colina emaranhada” de Darwin, metáfora inspirada pela “teia da vida” de Humboldt. Desemaranhar essa complexidade é uma tarefa desafiadora, mas factível, desde que você use ferramentas adequadas. A ciência de redes nos ajuda com excelentes ferramentas conceituais e operacionais.

Aug 17th 2026
4 Weeks
Networks Data Analysis Network Analysis
Details
Statistical Inference and Hypothesis Testing in Data Science Applications (Coursera) Coursera
University of Colorado Boulder

Statistical Inference and Hypothesis Testing in Data Science Applications (Coursera)

Statistics & Data Analysis Data Science

This course will focus on theory and implementation of hypothesis testing, especially as it relates to applications in data science. Students will learn to use hypothesis tests to make informed decisions from data. Special attention will be given to the general logic of hypothesis testing, error and error rates, power, simulation, and the correct computation and interpretation of p-values. Attention will also be given to the misuse of testing concepts, especially p-values, and the ethical implications of such misuse.

Aug 10th 2026
5-12 Weeks
Statistics Hypothesis Statistical Inference
Details
Introducción a Data Science: Programación Estadística con R (Coursera) Coursera
Universidad Nacional Autónoma de México

Introducción a Data Science: Programación Estadística con R (Coursera)

Statistics & Data Analysis Data Science

Este curso te proporcionará las bases del lenguaje de programación estadística R, la lengua franca de la estadística, el cual te permitirá escribir programas que lean, manipulen y analicen datos cuantitativos. Te explicaremos la instalación del lenguaje; también verás una introducción a los sistemas base de gráficos y al paquete para graficar ggplot2, para visualizar estos datos. Además también abordarás la utilización de uno de los IDEs más populares entre la comunidad de usuarios de R, llamado RStudio.

Aug 3rd 2026
4 Weeks
Data Analysis Data Science R Language
Details
Applied Text Mining in Python (Coursera) Coursera
University of Michigan

Applied Text Mining in Python (Coursera)

Statistics & Data Analysis Data Science

This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling).

Aug 17th 2026
4 Weeks
Programming Python Machine Learning
Details
Communicating Data Science Results (Coursera) Coursera
University of Washington

Communicating Data Science Results (Coursera)

Statistics & Data Analysis Data Science

Making predictions is not enough! Effective data scientists know how to explain and interpret their results, and communicate findings accurately to stakeholders to inform business decisions. Visualization is the field of research in computer science that studies effective communication of quantitative results by linking perception, cognition, and algorithms to exploit the enormous bandwidth of the human visual cortex. In this course you will learn to recognize, design, and use effective visualizations.

Aug 3rd 2026
3 Weeks
Ethics Cloud Computing Privacy
Details
Introduction to Neurohacking In R (Coursera) Coursera
Johns Hopkins University

Introduction to Neurohacking In R (Coursera)

Statistics & Data Analysis Data Science

Neurohacking describes how to use the R programming language and its associated package to perform manipulation, processing, and analysis of neuroimaging data. We focus on publicly-available structural magnetic resonance imaging (MRI). We discuss concepts such as inhomogeneity correction, image registration, and image visualization.

Aug 10th 2026
4 Weeks
Brain Neurology R Language
Details
Foundations of strategic business analytics (Coursera) Coursera
ESSEC Business School

Foundations of strategic business analytics (Coursera)

Management & Leadership Business

Who is this course for? This course is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. For example, it may be suited to experienced statisticians, analysts, engineers who want to move more into a business role. You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language and are familiar with databases and data analysis techniques such as regression, classification, and clustering.

Aug 3rd 2026
4 Weeks
Data Analysis Analytics Presentations
Details
Bayesian Statistics: Techniques and Models (Coursera) Coursera
University of California, Santa Cruz

Bayesian Statistics: Techniques and Models (Coursera)

Statistics & Data Analysis Data Science

This is the second of a two-course sequence introducing the fundamentals of Bayesian statistics. It builds on the course Bayesian Statistics: From Concept to Data Analysis, which introduces Bayesian methods through use of simple conjugate models. Real-world data often require more sophisticated models to reach realistic conclusions. This course aims to expand our “Bayesian toolbox” with more general models, and computational techniques to fit them.

Aug 10th 2026
5-12 Weeks
Monte Carlo Method ANOVA Statistical Modeling
Details