Oracle SQL for Data Science

Oracle SQL for Data Science, available at $54.99, has an average rating of 4.33, with 50 lectures, based on 6 reviews, and has 86 subscribers.

You will learn about Learn practical Oracle SQL skills and best practices for typical data science/data analytics tasks. Become more productive, making less mistakes, better managing the data and scripts, and stress free when performing complex data work. This course is ideal for individuals who are data scientist, data analyst, data engineer, statistician It is particularly useful for data scientist, data analyst, data engineer, statistician.

Enroll now: Oracle SQL for Data Science

Summary

Title: Oracle SQL for Data Science

Price: $54.99

Average Rating: 4.33

Number of Lectures: 50

Number of Published Lectures: 50

Number of Curriculum Items: 50

Number of Published Curriculum Objects: 50

Original Price: $34.99

Quality Status: approved

Status: Live

What You Will Learn

Learn practical Oracle SQL skills and best practices for typical data science/data analytics tasks. Become more productive, making less mistakes, better managing the data and scripts, and stress free when performing complex data work.

Who Should Attend

data scientist, data analyst, data engineer, statistician

Target Audiences

data scientist, data analyst, data engineer, statistician

In this course, Dr. Jay Zhou, an industrial practitioner and and competition winner, will share his Oracle SQL skills and best practices to perform typical data science/data analytics tasks. Hopefully, after taking the course you will become a better data scientist/data analyst. In your future project, you will be more efficient, make less mistakes, manage your data and scripts better and be stress free when performing complex data work. The course will NOT cover predictive model building. �

Course Curriculum

Chapter 1: Introduction

Lecture 1: About the Instructor

Lecture 2: Content of the Course

Lecture 3: About the SQL Scripts and Testing Data Used in the Course

Chapter 2: Why SQL for Data Science

Lecture 1: Why SQL for Data Science? – Part 1

Lecture 2: Why SQL for Data Science? – Part 2

Lecture 3: Why SQL for Data Science? – Part 3

Lecture 4: Why SQL for Data Science? – Part 4

Chapter 3: Typical Tasks for Data Science Project

Lecture 1: Typical Tasks for Data Science Project – Part 1

Lecture 2: Typical Tasks for Data Science Project – Part 2

Chapter 4: Data Validation and Understanding

Lecture 1: SQL for Data Validation and Understanding – Part 1

Lecture 2: SQL for Data Validation and Understanding – Part 2

Lecture 3: SQL for Data Validation and Understanding – Part 3

Lecture 4: SQL for Data Validation and Understanding – Part 3b

Lecture 5: SQL for Data Validation and Understanding – Part 4

Lecture 6: SQL for Data Validation and Understanding – Part 5

Lecture 7: SQL for Data Validation and Understanding – Part 6

Lecture 8: SQL for Data Validation and Understanding – Part 7

Lecture 9: SQL for Data Validation and Understanding – Part 8

Lecture 10: SQL for Data Validation and Understanding – Part 9

Lecture 11: SQL for Data Validation and Understanding – Part 10

Lecture 12: SQL for Data Validation and Understanding – Part 11

Lecture 13: SQL for Data Validation and Understanding – Part 12

Lecture 14: SQL for Data Validation and Understanding – Part 13

Lecture 15: SQL for Data Validation and Understanding – Part 14

Chapter 5: SQL for Data Cleansing and Preparation

Lecture 1: SQL for Data Cleansing and Preparation – Part 1

Lecture 2: SQL for Data Cleansing and Preparation – Part 2

Lecture 3: SQL for Data Cleansing and Preparation – Part 3

Lecture 4: SQL for Data Cleansing and Preparation – Part 4

Lecture 5: SQL for Data Cleansing and Preparation – Part 5

Lecture 6: SQL for Data Cleansing and Preparation – Part 6

Lecture 7: SQL for Data Cleansing and Preparation – Part 7

Lecture 8: SQL for Data Cleansing and Preparation – Part 8

Lecture 9: SQL for Data Cleansing and Preparation – Part 9

Lecture 10: SQL for Data Cleansing and Preparation – Part 10

Lecture 11: SQL for Data Cleansing and Preparation – Part 11

Lecture 12: SQL for Data Cleansing and Preparation – Part 12

Lecture 13: SQL for Data Cleansing and Preparation – Part 13

Lecture 14: SQL for Data Cleansing and Preparation – Part 14

Lecture 15: SQL for Data Cleansing and Preparation – Part 15

Chapter 6: Feature Variable Calculation

Lecture 1: Feature Variable Calculation – Part 1

Lecture 2: Feature Variable Calculation – Part 2

Lecture 3: Feature Variable Calculation – Part 3

Lecture 4: Feature Variable Calculation – Part 4

Lecture 5: Feature Variable Calculation – Part 5

Lecture 6: Feature Variable Calculation – Part 6

Lecture 7: Feature Variable Calculation – Part 7

Lecture 8: Feature Variable Calculation – Part 8

Lecture 9: Feature Variable Calculation – Part 9

Chapter 7: Summaries and Highlights

Lecture 1: Summaries and Highlights

Chapter 8: All Slides Used in the Course

Lecture 1: All Slides Used in the Course

Instructors

Jiang Zhou
Competition Winning Data Science Practitioner

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 2 votes
4 stars: 1 votes
5 stars: 3 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

Menu