Fundamentals of Data Analytics in the Public Sector with R from Coursera

Gain a foundational understanding of key terms and concepts in public administration and public policy while learning foundational programming techniques using the R programming language. You will learn how to execute functions to load, select, filter, mutate, and summarize data frames using the tidyverse libraries with an emphasis on the dplyr package. By the end of the course, you will create custom functions and apply them to population data which is commonly found in public sector analytics.

Throughout the course, you will work with authentic public datasets, and all programming can be completed in RStudio on the Coursera platform without additional software.

This is the first of four courses within the Data Analytics in the Public Sector with R Specialization. The series is ideal for current or early career professionals working in the public sector looking to gain skills in analyzing public data effectively. It is also ideal for current data analytics professionals or students looking to enter the public sector.

What's inside

Syllabus

Week 1 | Introduction to Data Analytics in the Public Sector with R

Welcome to the Data Analytics in the Public Sector with R and the First Course—Fundamentals of Public Sector Data Analysis with R. This week will be your orientation to the certificate and the first course. You will also get to learn several fundamental terms and their definitions that we will frequently use throughout the course and the certificate.

Week 2 | Core Functions of Public Administration and R Basics

Welcome to Week 2! You will start this week learning about the core functions of public administration and the role of data analytics in these functions. You will also start developing your skills with RStudio.

Week 3 | Survey Data Analysis with the Tidyverse

Welcome to Week 3! You will learn this week several analysis skills for survey data—one of the most common types of data in the public sector. These skills will allow you to not only understand how survey data could be designed and collected, but also how to analyze such data in RStudio and how to interpret them.

Week 4 | Population Data Analysis with Custom R functions

Welcome to Week 4! You will learn this week several analysis skills for population data—one of the most common types of data in the public sector that allow answering basic population questions. These skills will allow you to not only understand the sources of population data, but also how to analyze such data in RStudio and how to interpret them.

Week 5 | Public Sector Data Analytics in Practice

Welcome to Week 5, the last week in this course! This week, you will get to hear stories from public sector data analysts, with the goal of recognizing the challenges associated with the profession of a data analyst.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Helps you learn data analytics concepts and terms in a public administration context

Uses R programming language, which is popular for analyzing data in the public sector

Covers data manipulation and analysis skills that are valuable for public sector jobs

Includes hands-on exercises and projects that help you apply what you learn

Taught by instructors with expertise in public administration and data analytics

Introduces you to different types of data sources and how to work with them

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Fundamentals of Data Analytics in the Public Sector with R with these activities:

Review basic mathematics

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Reviewing basic mathematics will help you understand the statistical concepts covered in this course.

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Review basic arithmetic operations (addition, subtraction, multiplication, division)
Review basic algebra (solving equations, graphing lines)
Review basic calculus (derivatives, integrals)

Review Basic Statistics

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Strengthen your foundation in basic statistics to enhance your understanding of data analysis concepts covered in the course.

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Review concepts of probability distributions, sampling, and estimation.
Practice solving problems related to hypothesis testing and confidence intervals.
Utilize online resources or textbooks to refresh your knowledge on statistical methods.

Watch tutorials on R programming

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Watching tutorials on R programming will help you learn the basics of the language and how to use it for data analysis.

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Find tutorials on YouTube or other online platforms
Watch the tutorials and take notes
Practice the code examples shown in the tutorials

Two other activities

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Complete practice exercises on data analysis

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Completing practice exercises on data analysis will help you apply the concepts you learn in this course and improve your skills.

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Find practice exercises online or in textbooks
Complete the exercises and check your answers
Review your mistakes and learn from them

Create a data visualization project

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Creating a data visualization project will help you learn how to analyze and present data in a visually appealing way.

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Choose a dataset to work with
Clean and prepare the data
Create a data visualization using R or another programming language
Present your project to others

Career center

Learners who complete Fundamentals of Data Analytics in the Public Sector with R will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists collect, analyze, and interpret data to help businesses make informed decisions. They may work in a variety of industries, including healthcare, finance, and retail. This course may be useful for Data Scientists because it provides a foundation in data analysis techniques using the R programming language, which is commonly used in data science.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers design and develop machine learning models to help businesses solve problems and make informed decisions. They may work in a variety of industries, including healthcare, finance, and manufacturing. This course may be useful for Machine Learning Engineers because it provides a foundation in data analysis techniques using the R programming language, which is commonly used in machine learning.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to help businesses solve problems and make informed decisions. They may work in a variety of industries, including healthcare, finance, and manufacturing. This course may be useful for Operations Research Analysts because it provides a foundation in data analysis techniques using the R programming language, which is commonly used in operations research.

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Statistician

Statisticians collect, analyze, and interpret data to help businesses make informed decisions. They may work in a variety of industries, including healthcare, finance, and marketing. This course may be useful for Statisticians because it provides a foundation in data analysis techniques using the R programming language, which is commonly used in statistics.

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Data Architect

Data Architects design and implement data management systems to help businesses make informed decisions. They may work in a variety of industries, including healthcare, finance, and retail. This course may be useful for Data Architects because it provides a foundation in data analysis techniques using the R programming language, which is commonly used in data architecture.

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Software Engineer

Software Engineers design and develop software applications to help businesses solve problems and make informed decisions. They may work in a variety of industries, including healthcare, finance, and retail. This course may be useful for Software Engineers because it provides a foundation in data analysis techniques using the R programming language, which is commonly used in software development.

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Data Analyst

Data Analysts collect, clean, and analyze data to help businesses make informed decisions. They may work in a variety of industries, including healthcare, finance, and retail. This course may be useful for Data Analysts because it provides a foundation in data analysis techniques using the R programming language, which is commonly used in data analysis.

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Web Developer

Web Developers design and develop websites and web applications to help businesses solve problems and make informed decisions. They may work in a variety of industries, including healthcare, finance, and retail. This course may be useful for Web Developers because it provides a foundation in data analysis techniques using the R programming language, which is commonly used in web development.

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Risk Analyst

Risk Analysts identify and assess risks to help businesses make informed decisions. They may work in a variety of industries, including healthcare, finance, and insurance. This course may be useful for Risk Analysts because it provides a foundation in data analysis techniques using the R programming language, which is commonly used in risk analysis.

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Data Engineer

Data Engineers design and implement data pipelines to help businesses make informed decisions. They may work in a variety of industries, including healthcare, finance, and retail. This course may be useful for Data Engineers because it provides a foundation in data analysis techniques using the R programming language, which is commonly used in data engineering.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical techniques to help businesses make informed decisions. They may work in a variety of industries, including healthcare, finance, and insurance. This course may be useful for Quantitative Analysts because it provides a foundation in data analysis techniques using the R programming language, which is commonly used in quantitative analysis.

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Actuary

Actuaries use mathematical and statistical techniques to help businesses and individuals plan for the future. They may work in a variety of industries, including healthcare, finance, and insurance. This course may be useful for Actuaries because it provides a foundation in data analysis techniques using the R programming language, which is commonly used in actuarial science.

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Business Intelligence Analyst

Business Intelligence Analysts collect, analyze, and interpret data to help businesses make informed decisions. They may work in a variety of industries, including healthcare, finance, and retail. This course may be useful for Business Intelligence Analysts because it provides a foundation in data analysis techniques using the R programming language, which is commonly used in business intelligence.

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Market Research Analyst

Market Research Analysts collect and analyze data to help businesses understand their customers and make informed decisions. They may work for a variety of businesses, including consumer goods companies, retail stores, and advertising agencies. This course may be useful for Market Research Analysts because it provides a foundation in data analysis techniques using the R programming language, which is commonly used in market research.

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Public Health Analyst

Public Health Analysts research and analyze data to help promote public health. They may work for government agencies, non-profit organizations, or private companies. This course may be useful for Public Health Analysts because it provides a foundation in data analysis techniques using the R programming language, which is commonly used in public health research.

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