SQL for Data Science with R

SQL for Data Science with R

This course is part of multiple programs.

Instructor: Rav Ahuja

Access provided by MAHE Manipal

27,975 already enrolled

6 modules

Gain insight into a topic and learn the fundamentals.

192 reviews

Beginner level

Recommended experience

Flexible schedule

3 weeks at 10 hours a week

Learn at your own pace

95%

Most learners liked this course

6 modules

Gain insight into a topic and learn the fundamentals.

192 reviews

Beginner level

Recommended experience

Flexible schedule

3 weeks at 10 hours a week

Learn at your own pace

95%

Most learners liked this course

What you'll learn

Create and access a database instance on the cloud
Compose and execute basic SQL statements - SELECT, INSERT, UPDATE, DELETE, CREATE, DROP
Construct SQL statements to filter, sort, group results, use built-in functions, compose nested queries, access multiple tables
Analyze data from Jupyter using R and SQL by combining SQL and R skills to query real-world datasets

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

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Assessments

15 assignments¹

AI Graded see disclaimer

Taught in English

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There are 6 modules in this course

Much of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language which is used for communicating with and extracting data from databases. A working knowledge of databases and SQL is a must if you want to become a data scientist.

The purpose of this course is to introduce relational database concepts and 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. As such, you will work with real databases, real data science tools, and real-world datasets. Through a series of hands-on labs, you will practice building and running SQL queries. You will also learn how to access databases from Jupyter notebooks using SQL and R. No prior knowledge of databases, SQL, R, or programming is required. Anyone can audit this course at no charge. If you choose to take this course and earn the Coursera course certificate, you can also earn an IBM digital badge upon successful completion of the course.

Structured Query Language, or SQL, provides a standard language for selecting and manipulating data in a relational database. Understanding SQL is a foundational skill that you must have when applying data science principles in R because SQL is the key to helping you unlock insights about the information stored deep inside relational databases. In this module, you will learn some basic SQL statements and practice them hands-on on a live database.

What's included

5 videos2 readings2 assignments3 app items2 plugins

5 videos Total 17 minutes

Welcome to SQL for Data Science 5 minutes
SELECT Statement 4 minutes
COUNT, DISTINCT, LIMIT 2 minutes
INSERT Statement 3 minutes
UPDATE and DELETE Statements 3 minutes

2 readings Total 9 minutes

Course Overview 4 minutes
Module Summary: Getting Started with SQL 5 minutes

2 assignments Total 36 minutes

Graded Quiz: Getting Started with SQL 21 minutes
Practice Quiz: Getting Started with SQL 15 minutes

3 app items Total 70 minutes

Hands-on Lab: Simple SELECT Statements 20 minutes
Hands-on Lab: COUNT, DISTINCT, LIMIT 30 minutes
Hands-on Lab: INSERT, UPDATE, and DELETE 20 minutes

2 plugins Total 20 minutes

SELECT statement examples 5 minutes
SQL Cheat Sheet: Basics - SELECT, INSERT, UPDATE, DELETE, COUNT, DISTINCT, LIMIT 15 minutes

In this module, you will explore the fundamental concepts behind databases, tables, and the relationships between them. You will then create an instance of a database, discover SQL statements that allow you to create and manipulate tables, and then practice them on your own live database.

What's included

6 videos3 readings2 assignments3 app items2 plugins

6 videos Total 26 minutes

Introduction to Databases 4 minutes
Relational Database Concepts 6 minutes
Types of SQL statements (DDL vs. DML) 2 minutes
CREATE TABLE Statement 4 minutes
ALTER, DROP, and Truncate tables 4 minutes
How to create a Database instance on Cloud 6 minutes

3 readings Total 5 minutes

Module Summary: Introduction to Relational Databases and Tables 2 minutes
About this Optional Lesson 2 minutes
[Optional] Hands-on Lab Using IBM Db2 1 minute

2 assignments Total 31 minutes

Graded Quiz: Introduction to Relational Databases and Tables 21 minutes
Practice Quiz: Introduction to Relational Databases and Tables 10 minutes

3 app items Total 150 minutes

Hands-on Lab: CREATE, ALTER, TRUNCATE, DROP into Tables in MySQL using phpMyAdmin 60 minutes
Hands-on Lab: Create and Load Tables using SQL Scripts 60 minutes
Obtain IBM Cloud Feature Code and Activate Trial Account 30 minutes

2 plugins Total 10 minutes

Examples to CREATE and DROP tables 5 minutes
SQL Cheat Sheet: CREATE TABLE, ALTER, DROP, TRUNCATE 5 minutes

In this module, you will learn how to use string patterns and ranges to search data and how to sort and group data in result sets. You will also practice composing nested queries and execute select statements to access data from multiple tables.

What's included

7 videos4 readings4 assignments4 app items5 plugins

7 videos Total 31 minutes

Using String Patterns and Ranges 4 minutes
Sorting Result Sets 3 minutes
Grouping Result Sets 4 minutes
Built-in Database Functions 6 minutes
Date and Time Built-in Functions 3 minutes
Sub-Queries and Nested Selects 5 minutes
Working with Multiple Tables 6 minutes

4 readings Total 13 minutes

Summary: Refining Your Results 5 minutes
Summary: Functions, Multiple Tables, and Sub-queries 5 minutes
About this Optional Lesson 2 minutes
[Optional] Hands-on Lab Using IBM Db2 1 minute

4 assignments Total 72 minutes

Graded Quiz: Refining Your Results 21 minutes
Graded Quiz: Functions, Multiple Tables, and Sub-Queries 21 minutes
Practice Quiz: Refining Your Results 15 minutes
Practice Quiz: Functions, Multiple Tables, and Sub-queries 15 minutes

4 app items Total 240 minutes

Hands-on Lab: String Patterns, Sorting and Grouping 60 minutes
Hands-on Lab: Built-in functions 60 minutes
Hands-on Lab: Sub-queries and Nested SELECTs 60 minutes
Hands-on Lab: Working with Multiple Tables 60 minutes

5 plugins Total 65 minutes

Reading: Examples for String Patterns, Sorting, and Grouping 15 minutes
Reading: Examples for Built-in Functions 15 minutes
Reading: Examples for Sub Queries and Nested Queries 15 minutes
Reading: Examples for Multiple Tables 15 minutes
SQL Cheat Sheet: Intermediate - LIKE, ORDER BY, GROUP BY 5 minutes

In this module, you will learn the benefits of using R to connect to relational databases and how to persist R database objects in files. You’ll also learn some of the similarities between R data frames and relational databases, including how data types compare and when you must convert from one type to another to improve the effectiveness of your data analysis. Finally, you’ll learn different methods for connecting to a database from R.

What's included

10 videos3 readings4 assignments5 app items5 plugins

10 videos Total 27 minutes

Why use R with Relational Databases 2 minutes
R Persistence Options 1 minute
Terminology Comparison 2 minutes
Mapping Data between R and RDBMS 2 minutes
Database Design Considerations 3 minutes
Connectivity Options 3 minutes
Connecting with RJDBC 3 minutes
Connectivity using ODBC 3 minutes
RODBC in Detail 5 minutes
Metadata Discovery 4 minutes

3 readings Total 22 minutes

Summary & Highlights: R and Relational Databases 10 minutes
Summary & Highlights : Connecting to Databases from R 10 minutes
About this Optional Lesson 2 minutes

4 assignments Total 67 minutes

Graded Quiz: R and Relational Databases 21 minutes
Graded Quiz: Connecting to Databases from R 21 minutes
Practice Quiz: R and Relational Databases 10 minutes
Practice Quiz: Connecting to Databases from R 15 minutes

5 app items Total 160 minutes

Hands-on Lab: Review using Jupyter and R Dataframes 15 minutes
Hands-on Lab: Accessing Your Database using RJDBC 60 minutes
Hands-on Lab: Accessing Your Database with RSQLite 60 minutes
[Optional] Hands-on Lab: Accessing Your Database using RJDBC with DB2 10 minutes
[Optional] Hands-on Lab: Accessing your Database using RODBC with DB2 15 minutes

5 plugins Total 75 minutes

Cheat Sheet - R basics 15 minutes
Reading: Example for Connecting with RJDBC using SQLite 15 minutes
Reading: A Comprehensive Review of RSQLite 15 minutes
CheatSheet - Connecting to Databases using R 15 minutes
[Optional] Hands-on Lab: Create Db2 Service Credentials 15 minutes

In this module, you will learn the full process of accessing and querying databases using R. You’ll learn how to create the logical and physical model of the database and then implement the model by creating the physical database objects and loading them with data. Finally, you’ll examine an example of accessing and querying the database.

What's included

6 videos2 readings2 assignments2 app items2 plugins

6 videos Total 18 minutes

Working with Data 4 minutes
Database Design and Data Preparation 3 minutes
Creating Physical Database Objects 3 minutes
Loading the Data 1 minute
Querying Data (SQL SELECT) 4 minutes
Analyzing the Data 3 minutes

2 readings Total 7 minutes

Summary and Highlights: Working with Database Objects using R 5 minutes
About this Optional Lesson 2 minutes

2 assignments Total 31 minutes

Graded Quiz: Working with Database Objects using R 21 minutes
Practice Quiz: Working with Database Objects using R 10 minutes

2 app items Total 90 minutes

Hands-on Lab: Creating and Querying Database Objects from R using RSQLite with SQLite 60 minutes
[Optional] Hands-on Lab: Creating and Querying Database Objects from R using RODBC with DB2 30 minutes

2 plugins Total 30 minutes

Reading: Example for Creating and querying databases with SQLite using R 15 minutes
CheatSheet- Creating Database Objects & Querying Data from R 15 minutes

In this assignment, you will be working with multiple real-world datasets for the Canadian Crop Data and Exchange Rates. You will be asked questions that will help you understand the data just as you would in the real world. You will be assessed on the correctness of your SQL queries and results.

What's included

1 reading1 assignment1 peer review5 app items2 plugins

1 reading Total 2 minutes

Congratulations & Next Steps 2 minutes

1 assignment Total 50 minutes

Final Exam 50 minutes

1 peer review Total 60 minutes

Option 2: Peer Graded - Final Project Submission and Evaluation 60 minutes

5 app items Total 255 minutes

Option 1: AI Graded - Final Project: Submission and Evaluation 60 minutes
Hands-on Lab: Practice Querying Real World Datasets using RSQLite with SQLite 60 minutes
[Optional] Hands-on Lab: Practice Querying Real World Datasets using RODBC with DB2 30 minutes
Lab for Final Project - Data Analytics for Canadian Crop Production Data Set 60 minutes
[Optional] Jupyter Notebook with Problems for Peer Reviewed Assignment using RODBC with DB2 45 minutes

2 plugins Total 25 minutes

Final Project Overview 20 minutes
Reading: Final Project Submission Guidelines and Deliverables 5 minutes

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Instructor

Instructor ratings

(68 ratings)

Rav Ahuja

IBM

55 Courses 4,816,685 learners

Offered by

IBM

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Reviewed on Feb 12, 2025

The content and pacing were excellent. I came into the course with plenty of PL/SQL experience, and left feeling like I had a strong foundation with how SQL works in R.

Reviewed on Mar 4, 2022

This skills in this course are easy to learn, the simplicity of the materials is what I like the most about IBM courses.

Reviewed on Jan 22, 2025

Great graphics and easy to understand explanation. I'm grateful to Coursera for this wonderful opportunity

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