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Best Online SQL Courses for Data Science

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Best online SQL Courses for Data Science
Best Online SQL Courses for Data Science

Learn SQL Basics for Data Science Specialization

Provider: University of California

This Specialization is intended for a learner with no previous coding experience seeking to develop SQL query fluency.

Through four progressively more difficult SQL projects with data science applications, you will cover topics such as SQL basics, data wrangling, SQL analysis, AB testing, distributed computing using Apache Spark, Delta Lake and more.

These topics will prepare you to apply SQL creatively to analyze and explore data; demonstrate efficiency in writing queries; create data analysis datasets; conduct feature engineering, use SQL with other data analysis and machine learning toolsets; and use SQL with unstructured data sets. 

Skills you will gain:

  • Data Analysis
  • Apache Spark
  • Delta Lake
  • SQL
  • Data Science
  • Sqlite
  • A/B Testing
  • Query String
  • Predective Analytics
  • Presentation Skills
  • Creating metrics
  • Exploratory Data Analysis

Things You will Learn:

  • U​se SQL commands to filter, sort, & summarize data; manipulate strings, dates, & numerical data from different sources for analysis
  • A​ssess and create datasets to solve your business questions and problems using SQL
  • U​se the collaborative Databricks workspace and create an end-to-end pipeline that reads data, transforms it, and saves the result
  • Develop a project proposal & select your data, perform statistical analysis & develop metrics, and p​resent your findings & make recommendations

Courses:

  • SQL for Data Science
  • Data Wrangling, Analysis, and AB testing with SQL
  • Distributed computing with Spark SQL
  • SQL for Data Science Capstone project

Interested to enroll for this course, then watch a free demo

SQL for Data Science

Provider: University of California

This course is designed to give you a primer in the fundamentals of SQL and working with data so that you can begin analyzing it for data science purposes.

You will begin to ask the right questions and come up with good answers to deliver valuable insights for your organization. This course starts with the basics and assumes you do not have any knowledge or skills in SQL.

It will build on that foundation and gradually have you write both simple and complex queries to help you select data from tables.  You’ll start to work with different types of data like strings and numbers and discuss methods to filter and pare down your results. 

You will create new tables and be able to move data into them. You will learn common operators and how to combine the data. You will use case statements and concepts like data governance and profiling.

You will discuss topics on data, and practice using real-world programming assignments. You will interpret the structure, meaning, and relationships in source data and use SQL as a professional to shape your data for targeted analysis purposes. 

Although we do not have any specific prerequisites or software requirements to take this course, a simple text editor is recommended for the final project. So what are you waiting for? This is your first step in landing a job in the best occupation in the US and soon the world!

What you will learn:

  • Identify a subset of data needed from a column or set of columns and write a SQL query to limit to those results.
  • U​se SQL commands to filter, sort, and summarize data.
  • Create an analysis table from multiple queries using the UNION operator.
  • Manipulate strings, dates, & numeric data using functions to integrate data from different sources into fields with the correct format for analysis.

Courses / Topics:

  • Getting Started and Selecting & Retrieving Data with SQL
  • Filtering, Sorting, and Calculating Data with SQL
  • Subqueries and Joins in SQL
  • Modifying and Analyzing Data with SQL

Interested to enroll then watch a free demo

SQL for Data Science with R:

Provider: IBM

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.

Skills you will gain:

  • Data Science
  • Select (SQL)
  • Relational Data Bases
  • R Programming
  • Tables (Databases)

What you will 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

Syllabus:

  • Getting started with SQL
  • Introduction to Relational Databases, and tables
  • Intermediate SQL
  • Getting Started with Databases using R
  • Working with Database Objects Using R
  • Course Project

Interested to enroll, then watch a free demo

Data Wrangling, Analysis and AB Testing with SQL

Provider: University of California

This course allows you to apply the SQL skills taught in “SQL for Data Science” to four increasingly complex and authentic data science inquiry case studies. We’ll learn how to convert timestamps of all types to common formats and perform date/time calculations.

We’ll select and perform the optimal JOIN for a data science inquiry and clean data within an analysis dataset by deduping, running quality checks, backfilling, and handling nulls.

ou’ll learn how to segment and analyze data per segment using windowing functions and use case statements to execute conditional logic to address a data science inquiry. We’ll also describe how to convert a query into a scheduled job and how to insert data into a date partition.

Finally, given a predictive analysis need, we’ll engineer a feature from raw data using the tools and skills we’ve built over the course. The real-world application of these skills will give you the framework for performing the analysis of an AB test.

Syllabus:

  • Data of Unknown quality
  • Creating clean datasets
  • SQL Problem solving
  • Case study: AB Testing

Interested to enroll, then start with a free demo

Databases and SQL for Data Science with Python

Provider: IBM

The purpose of this course is to introduce relational database concepts and help you learn and apply foundational knowledge of the SQL language. 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 Python.

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

Skills you will learn:

  • Analyze data within a database using SQL and Python.
  • Create a relational database on Cloud and work with tables.
  • Compare and contrast DDL to DML.
  • Write SQL statements including SELECT, INSERT, UPDATE, and DELETE.

Syllabus:

  • Getting started with SQL
  • Introduction to Relational Databases, and tables
  • Intermediate SQL
  • Accessing Database using Python
  • Course assignment
  • Bonus Module: Advanced SQL for Data Engineering

LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

interested to enroll, then start with a free demo

Data Warehousing for Business Intelligence Specialization:

Provider: University of Colorado

This Specialization covers data architecture skills that are increasingly critical across a broad range of technology fields.

You’ll learn the basics of structured data modeling, gain practical SQL coding experience, and develop an in-depth understanding of data warehouse design and data manipulation. You’ll have the opportunity to work with large data sets in a data warehouse environment to create dashboards and Visual Analytics.

You will use MicroStrategy, a leading BI tool, OLAP (online analytical processing) and Visual Insights capabilities to create dashboards and Visual Analytics.

In the final Capstone Project, you’ll apply your skills to build a small, basic data warehouse, populate it with data, and create dashboards and other visualizations to analyze and communicate the data to a broad audience.

Skills you will gain:

  • Data Visualization
  • Data Warehouse
  • SQL
  • Database design
  • Entity-Relationship model
  • Database
  • Extraction, transformation, and Loading
  • Data Integration
  • Datawarehousing
  • Business Intelligence

Courses:

  • Database management essentials
  • Data warehouse concepts, Design and Data Integration
  • Relational Database support for Dataware houses
  • Business Intelligence concepts, Tools and Applications
  • Design and Build a Data Warehouse for Business Intelligence for implementation

interested to enroll, then start with a free demo

Modern Big Data Analysis with SQL Specialization:

Provider: Cloudera

Maybe you are new to SQL and you want to learn the basics. Or maybe you already have some experience using SQL to query smaller-scale data with relational databases. Either way, if you are interested in gaining the skills necessary to query big data with modern distributed SQL engines, this Specialization is for you.

Most courses that teach SQL focus on traditional relational databases, but today, more and more of the data that’s being generated is too big to be stored there, and it’s growing too quickly to be efficiently stored in commercial data warehouses. Instead, it’s increasingly stored in distributed clusters and cloud storage. These data stores are cost-efficient and infinitely scalable.

To query these huge datasets in clusters and cloud storage, you need a newer breed of SQL engine: distributed query engines, like Hive, Impala, Presto, and Drill. These are open source SQL engines capable of querying enormous datasets. This Specialization focuses on Hive and Impala, the most widely deployed of these query engines.

Skills you will gain:

  • Cloud Storage
  • Data Analysis
  • Big Data
  • Cloudera
  • SQL
  • Database
  • Data warehousing
  • Apache Hive
  • Apache Impala
  • Data management
  • Distributed File Systems

What You Will Learn:

  • Distinguish operational from analytic databases, and understand how these are applied in big data
  • Understand how database and table design provides structures for working with data
  • Appreciate how differences in volume and variety of data affects your choice of an appropriate database system
  • Recognize the features and benefits of SQL dialects designed to work with big data systems for storage and analysis

Courses:

  • Foundations for Bigdata Analysis with SQL
  • Analyzing Big Data with SQL
  • Managing big data in clusters and Cloud storage

Interested to enroll then start with a free demo

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