SQL for Data Science with R from edX

A majority of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language for communicating with and extracting data from databases. A working knowledge of databases and the SQL language is a must if you want to become a data scientist. The purpose of this course is to introduce relational database concepts and to help you learn and apply foundational knowledge of the SQL and R languages. It is also intended to get you started with performing SQL access in a data science environment.

The emphasis in this course is on hands-on and practical learning, which means you will work with real databases, real data science tools, and real-world datasets. You will also create a database instance in the cloud. Through a series of hands-on labs you will practice building and running SQL queries. And you will learn how to access databases from Jupyter notebooks using SQL and R.

No prior knowledge of databases, SQL, R, or programming is required.

What you'll learn

Create and access a database instance on cloud
Write basic SQL statements: CREATE, DROP, SELECT, INSERT, UPDATE, DELETE
Filter, sort, group results, use built-in functions, compose nested queries, access multiple tables
Access databases from Jupyter using R and SQL to query real-world datasets

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Suitable for learners of all skill levels, from beginners new to data science to seasoned professionals looking to build relational database concepts

Helps you learn SQL and R, which are languages essential to becoming a data scientist

Utilises real-world datasets and databases, providing practical experience in working with real-world data

Instructors are Rav Ahuja

Reviews summary

Practical sql and r for data science

According to students, this course offers a strong, hands-on introduction to SQL and R for data science, particularly beneficial for beginners with no prior programming experience. Learners appreciate the practical emphasis on creating and accessing cloud database instances and performing real-world data queries within Jupyter notebooks. The curriculum effectively teaches foundational SQL statements and their application to complex data manipulation. While providing a solid groundwork for data science workflows, some feedback suggests the R integration primarily focuses on database connectivity rather than advanced R programming for data analysis.

Blends SQL and R for data science workflows.

"The integration of SQL queries with R in Jupyter notebooks was a key highlight for me."

"I learned how to seamlessly access and manipulate data from databases using both languages."

"This course effectively connects essential database skills directly to practical data science tasks."

Accessible for those with no prior background.

"As a complete beginner to databases and programming, I found the course easy to follow and understand."

"The assertion that no prior knowledge is needed truly holds; it laid a solid foundation."

"It's a great starting point for anyone looking to enter data science with SQL and R."

Practical, real-world application of skills.

"I loved the hands-on labs and working with real datasets."

"Creating and accessing a cloud database instance was incredibly practical and insightful."

"The emphasis on applying SQL and R in Jupyter made the learning very useful for real-world tasks."

R usage primarily for database access.

"My expectation was more R programming, but it's mainly for SQL connection and basic data retrieval."

"While useful for database interaction, don't anticipate extensive R data analysis skills from this course alone."

"The R portion felt somewhat limited to just connecting to databases rather than broader scripting."

Focuses on foundations, not advanced topics.

"The course provides a good starting point, but it primarily covers foundational SQL concepts."

"I felt it could have gone deeper into more complex SQL queries or database optimization techniques."

"Don't expect advanced database administration skills from this introductory course."

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 SQL for Data Science with R with these activities:

Review PostgreSQL concepts

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Reviewing PostgreSQL concepts will help you refresh your knowledge and ensure you have a solid foundation for the course.

Browse courses on PostgreSQL

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Reread your notes from a previous course on PostgreSQL.
Watch online tutorials on PostgreSQL basics.
Complete practice exercises on PostgreSQL queries.

Complete Coursera Tutorial on SQL

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Supplement course material with an introductory tutorial on SQL.

Browse courses on SQL

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Create a Coursera account.
Enroll in the "SQL for Data Science" tutorial.
Complete all modules and quizzes.

Review Basic R Programming

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Ensure proficiency in R programming before starting the course.

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Go over R syntax and data structures.
Practice writing basic R functions.
Complete a small R programming project.

Eight other activities

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Complete SQL and R tutorials

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Completing SQL and R tutorials will help you develop the skills necessary to work with databases and data sets.

Browse courses on SQL

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Find online tutorials on SQL and R for beginners.
Follow the tutorials step-by-step and complete the exercises.
Ask questions and seek help if you encounter any difficulties.

Read "Database Systems"

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Review concepts in database management to prepare for the course.

View Database Systems: The Complete Book on Amazon

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Purchase the book or access it online.
Read at least 3 chapters.
Summarize the key points of each chapter.

Practice SQL queries

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Regular practice with SQL queries will improve your proficiency and confidence in working with databases.

Browse courses on SQL

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Find online platforms or resources that offer SQL practice exercises.
Solve a variety of SQL queries of varying difficulty levels.
Review your answers and identify areas for improvement.

SQL Practice Problems

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Practice SQL queries to improve understanding and confidence.

Browse courses on SQL

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Find a set of practice problems online.
Attempt to solve the problems without looking at the solutions.
Check your solutions against the provided answers.

Join a SQL Study Group

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Enhance understanding through collaborative learning with peers.

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Find or create a study group with other students taking the course.
Meet regularly to discuss concepts, work on practice problems, and help each other with assignments.
Take turns leading discussions and presenting material.

Create a Database Project Proposal

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Apply theoretical knowledge by proposing a database project.

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Identify a problem or opportunity that can be solved using a database.
Design the database schema.
Write a proposal outlining your project plan, including objectives, methodology, and expected outcomes.

Volunteer at a Local Data Science Organization

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Gain practical experience and expand networking within the data science field.

Browse courses on Data Science

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Identify data science organizations in your area.
Contact the organizations to inquire about volunteer opportunities.
Participate in projects or events related to data science.
Network with professionals in the field.

Contribute to Open-Source SQL Projects

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Deepen understanding of SQL by contributing to real-world projects.

Browse courses on Open Source

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Find open-source SQL projects on platforms like GitHub.
Identify areas where you can contribute based on your skill level.
Submit pull requests with your code contributions.

Career center

Learners who complete SQL for Data Science with R will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use programming and analytical skills to solve complex problems and extract meaningful insights from data. Industries across the board are seeking skilled Data Scientists to aid in operational efficiency and problem-solving. This SQL for Data Science with R course can help you gain experience with using SQL and R to perform complex queries and analyze real-world datasets. Some future employers may require a Master's or PhD in Data Science or related field.

See salaries and explore the career path for Data Scientist

Database Administrator

Database Administrators ensure database systems operate smoothly, efficiently, and securely. As the amount of data companies collect continues to grow, the need for skilled Database Administrators will continue to rise. This SQL for Data Science with R course can help you build a foundation in database management, as you'll learn how to create and access a database instance on cloud, write basic SQL statements, and more.

See salaries and explore the career path for Database Administrator

Data Analyst

Data Analysts help companies turn raw information into usable insights. As a fast-growing field, it's expected to see a 20% job growth between 2019 and 2029. This course in SQL for Data Science with R can help you build a foundation in data analysis, as you'll learn how to communicate with and extract data from databases. Some future employers may even require a Master's degree in a related field.

See salaries and explore the career path for Data Analyst

Market Researcher

Market Researchers gather and analyze data about markets, customers, and competitors. They use this information to help businesses make informed decisions about product development, marketing campaigns, and other business strategies. This SQL for Data Science with R course may be helpful for those considering a career in Market Research, as you'll learn how to write basic SQL statements and use SQL and R to access databases and analyze real-world datasets.

See salaries and explore the career path for Market Researcher

Statistician

Statisticians collect, analyze, interpret, and present data. They use their skills to help businesses and organizations make informed decisions. This SQL for Data Science with R course may be helpful for those considering a career in Statistics, as you'll learn how to write basic SQL statements and use SQL and R to access databases and analyze real-world datasets.

See salaries and explore the career path for Statistician

Software Engineer

Software Engineers design, develop, and maintain software applications. With the increasing importance of data in software development, Software Engineers with skills in data analysis and database management are in high demand. This SQL for Data Science with R course may be useful for those considering a career in Software Engineering, as you'll learn how to write basic SQL statements and use SQL and R to access databases and analyze real-world datasets.

See salaries and explore the career path for Software Engineer

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze data and make predictions about financial markets. They play a vital role in helping investment firms make informed investment decisions. This SQL for Data Science with R course may be helpful for those considering a career in Quantitative Finance, as you'll learn how to write basic SQL statements and use SQL and R to access databases and analyze real-world datasets.

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Data Architect

Data Architects design and manage the architecture of data systems. They work with stakeholders to understand business requirements and translate those requirements into technical specifications. This SQL for Data Science with R course may be helpful for those considering a career in Data Architecture, as you'll learn how to write basic SQL statements and use SQL and R to access databases and analyze real-world datasets.

See salaries and explore the career path for Data Architect

Machine Learning Engineer

Machine Learning Engineers design, develop, and maintain machine learning models. They work on a variety of projects, such as developing self-driving cars, improving medical diagnosis, and personalizing online experiences. This SQL for Data Science with R course may be helpful for those considering a career in Machine Learning Engineering, as you'll learn how to write basic SQL statements and use SQL and R to access databases and analyze real-world datasets.

See salaries and explore the career path for Machine Learning Engineer

Information Security Analyst

Information Security Analysts protect computer networks and systems from unauthorized access, use, disclosure, disruption, modification, or destruction. With the increasing amount of data being stored and processed electronically, Information Security Analysts are in high demand. This SQL for Data Science with R course may be helpful for those considering a career in Information Security, as you'll learn how to write basic SQL statements and use SQL and R to access databases and analyze real-world datasets.

See salaries and explore the career path for Information Security Analyst

Actuary

Actuaries use mathematical and statistical models to assess risk and uncertainty. They work in a variety of industries, including insurance, finance, and healthcare. This SQL for Data Science with R course may be helpful for those considering a career as an Actuary, as you'll learn how to write basic SQL statements and use SQL and R to access databases and analyze real-world datasets.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex problems in a variety of industries, including manufacturing, transportation, and healthcare. This SQL for Data Science with R course may be helpful for those considering a career as an Operations Research Analyst, as you'll learn how to write basic SQL statements and use SQL and R to access databases and analyze real-world datasets.

See salaries and explore the career path for Operations Research Analyst

Risk Analyst

Risk Analysts identify, assess, and manage risks. They work in a variety of industries, including finance, insurance, and healthcare. This SQL for Data Science with R course may be helpful for those considering a career as a Risk Analyst, as you'll learn how to write basic SQL statements and use SQL and R to access databases and analyze real-world datasets.

See salaries and explore the career path for Risk Analyst

Data Engineer

Data Engineers design, build, and maintain data pipelines. They work on the infrastructure that supports data analysis, machine learning, and other data-driven initiatives. This SQL for Data Science with R course may be useful, as it will help you to learn about database concepts and how to communicate with and extract data from databases.

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Business Analyst

Business Analysts help organizations understand their business needs and develop solutions to improve their operations. With a growing emphasis on data-driven decision-making, Business Analysts are in high demand. This SQL for Data Science with R course may be useful for getting started on your path to becoming a Business Analyst, as you'll learn how to write basic SQL statements and use SQL and R to access databases and analyze real-world datasets.

See salaries and explore the career path for Business Analyst