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

Building a Data Science Team (Coursera) Coursera
Johns Hopkins University

Building a Data Science Team (Coursera)

Data science is a team sport. As a data science executive it is your job to recruit, organize, and manage the team to success. In this one-week course, we will cover how you can find the right people to fill out your data science team, how to organize them to give them the best chance to feel empowered and successful, and how to manage your team as it grows.

Oct 19th 2026
1 Week
Machine Translation (Coursera) Coursera
Karlsruhe Institute of Technology - KIT

Machine Translation (Coursera)

Welcome to the CLICS-Machine Translation MOOC. This MOOC explains the basic principles of machine translation. Machine translation is the task of translating from one natural language to another natural language. Therefore, these algorithms can help people communicate in different languages. Such algorithms are used in common applications, from Google Translate to apps on your mobile device.

Oct 26th 2026
5-12 Weeks
Basic Statistics (Coursera) Coursera
University of Amsterdam

Basic Statistics (Coursera)

Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This course will also prepare you for the next course in the specialization - the course Inferential Statistics. In the first part of the course we will discuss methods of descriptive statistics. You will learn what cases and variables are and how you can compute measures of central tendency (mean, median and mode) and dispersion (standard deviation and variance). Next, we discuss how to assess relationships between variables, and we introduce the concepts correlation and regression.

Oct 26th 2026
5-12 Weeks
Designing, Running, and Analyzing Experiments (Coursera) Coursera
University of California, San Diego

Designing, Running, and Analyzing Experiments (Coursera)

You may never be sure whether you have an effective user experience until you have tested it with users. In this course, you’ll learn how to design user-centered experiments, how to run such experiments, and how to analyze data from these experiments in order to evaluate and validate user experiences. You will work through real-world examples of experiments from the fields of UX, IxD, and HCI, understanding issues in experiment design and analysis.

Oct 19th 2026
5-12 Weeks
A Crash Course in Data Science (Coursera) Coursera
Johns Hopkins University

A Crash Course in Data Science (Coursera)

By now you have definitely heard about data science and big data. In this one-week class, we will provide a crash course in what these terms mean and how they play a role in successful organizations. This class is for anyone who wants to learn what all the data science action is about, including those who will eventually need to manage data scientists. The goal is to get you up to speed as quickly as possible on data science without all the fluff. We've designed this course to be as convenient as possible without sacrificing any of the essentials.

Oct 19th 2026
1 Week
Inferential Statistics (Coursera) Coursera
Duke University

Inferential Statistics (Coursera)

This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data.

Oct 26th 2026
5-12 Weeks
Introduction to Neurohacking In R (Coursera) Coursera
Johns Hopkins University

Introduction to Neurohacking In R (Coursera)

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.

Nov 2nd 2026
4 Weeks
The R Programming Environment (Coursera) Coursera
Johns Hopkins University

The R Programming Environment (Coursera)

This course provides a rigorous introduction to the R programming language, with a particular focus on using R for software development in a data science setting. Whether you are part of a data science team or working individually within a community of developers, this course will give you the knowledge of R needed to make useful contributions in those settings.

Oct 19th 2026
4 Weeks
Data Science Math Skills (Coursera) Coursera
Duke University

Data Science Math Skills (Coursera)

Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time.

Nov 2nd 2026
4 Weeks
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)

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.

Nov 2nd 2026
4 Weeks
Use Tableau for your Data Science Workflow (Coursera) Coursera
Edureka

Use Tableau for your Data Science Workflow (Coursera)

Learn Tableau fundamentals, advanced visualizations, and integration with data science tools. Elevate your skills in creating impactful dashboards. Enroll now for hands-on experience and master the art of data storytelling. Unlock the potential for advanced analytics, exploring correlations and trends within your data. Build interactive dashboards that tell compelling data stories, utilizing filters, parameters, and actions for user engagement.

Nov 2nd 2026
1 Week
Social Media Data Analytics (Coursera) Coursera
University of Washington

Social Media Data Analytics (Coursera)

Learner Outcomes: After taking this course, you will be able to: utilize various Application Programming Interface (API) services to collect data from different social media sources such as YouTube, Twitter, and Flickr; process the collected data - primarily structured - using methods involving correlation, regression, and classification to derive insights about the sources and people who generated that data; analyze unstructured data - primarily textual comments - for sentiments expressed in them; use different tools for collecting, analyzing, and exploring social media data for research and development purposes.

Oct 19th 2026
4 Weeks