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IBM - SQL for Data Science with R 

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SQL for Data Science with R
 at 
Coursera 
Overview

Duration

14 hours

Start from

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Total fee

Free

Mode of learning

Online

Difficulty level

Beginner

Official Website

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Credential

Certificate

SQL for Data Science with R
 at 
Coursera 
Highlights

  • Shareable Certificate Earn a Certificate upon completion
  • 100% online Start instantly and learn at your own schedule.
  • Flexible deadlines Reset deadlines in accordance to your schedule.
  • Beginner Level
  • Approx. 14 hours to complete
  • English Subtitles: English
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SQL for Data Science with R
 at 
Coursera 
Course details

More about 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. You will create a database instance in the cloud. 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.
  • This course is part of multiple programs
  • 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:
  • Applied Data Science with R Specialization
  • IBM Data Analytics with Excel and R Professional Certificate
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SQL for Data Science with R
 at 
Coursera 
Curriculum

Getting Started with SQL

Welcome to SQL for Data Science

SELECT Statement

COUNT, DISTINCT, LIMIT

INSERT Statement

UPDATE and DELETE Statements

Summary & Highlights

Practice Quiz

Graded Quiz: Basic SQL

Introduction to Relational Databases and Tables

Introduction to Databases

Relational Database Concepts

How to create a Database instance on Cloud

Types of SQL statements (DDL vs. DML)

CREATE TABLE Statement

ALTER, DROP, and Truncate tables

Summary & Highlights

Practice Quiz

Graded Quiz: Relational DB Concepts and Tables

Intermediate SQL

Using String Patterns and Ranges

Sorting Result Sets

Grouping Result Sets

Built-in Database Functions

Date and Time Built-in Functions

Sub-Queries and Nested Selects

Working with Multiple Tables

Summary & Highlights

Summary & Highlights

Practice Quiz

Graded Quiz: Refining Your Results

Practice Quiz

Graded Quiz: Functions, Sub-Queries, Multiple Tables

Getting Started with Databases using R

Why use R with Relational Databases

R Persistence Options

Terminology Comparison

Mapping Data between R and RDBMS

Database Design Considerations

Connectivity Options

Connecting with RJDBC

Connectivity using ODBC

RODBC in Detail

Metadata Discovery

Summary & Highlights

Summary & Highlights

Practice Quiz

Graded Quiz: R and Relational Databases

Practice Quiz

Graded Quiz: Connecting to Databases from R

Working with Database Objects using R

Working with Data

Database Design and Data Preparation

Creating Physical Database Objects

Loading the Data

Querying Data (SQL SELECT)

Analyzing the Data

Summary & Highlights

Practice Quiz

Graded Quiz: Creating Database Objects and Querying Data from R

Course Project

Congratulations & Next Steps

SQL for Data Science with R
 at 
Coursera 
Admission Process

    Important Dates

    May 25, 2024
    Course Commencement Date

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