Databases and SQL for Data Science with Python

Course Feature
  • Cost
    Free
  • Provider
    Coursera
  • Certificate
    Paid Certification
  • Language
    English
  • Start Date
    10th Jul, 2023
  • Learners
    No Information
  • Duration
    No Information
  • Instructor
    Rav Ahuja and Hima Vasudevan
Next Course
3.0
0 Ratings
Data Scientists, Data Analysts and Data Engineers must have a working knowledge of SQL to effectively communicate with and extract data from databases. This course provides an introduction to databases and SQL for data science with Python.
Show All
Course Overview

❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [February 21st, 2023]

What skills and knowledge will you acquire during this course?
This course will provide learners with the skills and knowledge to write foundational SQL statements, filter result sets, create and alter tables, and access databases as a data scientist. Learners will also gain experience building SQL queries, working with real databases on the Cloud, and using real data science tools. Additionally, learners may gain knowledge of other database technologies such as MongoDB or PostgreSQL.

How does this course contribute to professional growth?
This course provides a comprehensive introduction to SQL and its use in data science, allowing learners to develop foundational SQL statements, filter result sets, create and alter tables, and access databases as a data scientist. Through hands-on labs and projects, learners will gain practical experience in building SQL queries, working with real databases on the Cloud, and using real data science tools. This course can contribute to professional growth by providing learners with the skills necessary to pursue a career in data science, data engineering, or data analysis. Additionally, learners can use the skills they learn to develop their own applications or websites.

Is this course suitable for preparing further education?
This course provides a comprehensive introduction to SQL and its use in data science, making it suitable for preparing further education. Learners will gain foundational knowledge of SQL statements, filtering result sets, creating and altering tables, and accessing databases. Through hands-on labs and projects, learners will practice building SQL queries, work with real databases on the Cloud, and use real data science tools. Possible development paths include data science, data engineering, or data analysis, as well as developing their own applications or websites. To supplement this course, learners may want to explore additional courses in Python, data science, or database management, as well as other database technologies such as MongoDB or PostgreSQL. Additionally, learners may want to practice their skills by working on projects or participating in hackathons.

Show All
Recommended Courses
master-sql-for-data-science-5087
Master SQL for Data Science
3.0
LinkedIn Learning 1 learners
Learn More
This course is perfect for data science project specialists looking to expand their knowledge of SQL and related tool sets and platforms. Learn how to master the skills needed to work with SQL engineers and discover how your SQL knowledge applies to data science projects. With this course, you will be able to construct an expanded skill set optimized for data science work.
free microsoft-azure-databricks-for-data-engineering-5091
Microsoft Azure Databricks for Data Engineering
4.6
Udemy 4,560 learners
Learn More
This course is designed to help IT professionals become Azure Data Engineers and prepare for the Microsoft DP-203 exam. It covers the power of Apache Spark and Azure Databricks, and how to use them to run large data engineering workloads in the cloud. You will learn how to work with large amounts of data from multiple sources, and how Azure Databricks supports day-to-day data-handling functions. This course is part of a Specialization intended for Data Engineers and developers, and includes a practice exam to help you prepare for the exam. With the help of experienced mentors, you will gain the knowledge and expertise to design and implement data solutions that use Microsoft Azure data services.
free tech-talk-top-tuning-tips-for-spark-30-and-delta-lake-on-databricks-5092
Tech Talk: Top Tuning Tips for Spark 30 and Delta Lake on Databricks
1.5
Youtube 0 learners
Learn More
This Tech Talk provides an overview of the best tuning tips for Apache Spark 3.0 and Delta Lake on Databricks. Attendees will learn how to pick the best join strategy, use partition pruning and data skipping, optimize merges, and pick good instance types. They will also gain insight into the advantages of using Apache Spark 3.0 and AQE, as well as the benefits of Databricks Delta Lake and Stats.
databricks-fundamentals-apache-spark-core-5093
Databricks Fundamentals & Apache Spark Core
4.4
Udemy 20,440 learners
Learn More
This course provides an introduction to Databricks and Apache Spark 2.4 and 3.0.0. It covers the fundamentals of Apache Spark, how to write Spark applications using Scala and SQL, and how to use the DataFrame API and SQL to perform data manipulation tasks. It also explains how Apache Spark runs on a cluster with multiple nodes, and how to use UDFs with the DataFrame API or Spark SQL. Finally, it covers how to write DataFrames to external storage systems. With this course, you will gain the knowledge and skills to use Apache Spark and Databricks to process Big Data.
Favorites (0)
Favorites
0 favorite option

You have no favorites

Name delet