Learn SQL Basics for Data Science Specialization on Coursera

Online

Created by UC Davis Continuing and Professional Education and hosted on the Coursera platform, this is an online course consisting of pre-recorded video lectures, auto-graded and peer-reviewed assignments and community discussion forums. This specialization program is self-paced and designed to help you master a specific career skill in as little as 4-6 months.

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, 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.

Section Number

000WEB104

Instruction Method

Online class

Section Notes

Enrollments are accepted on a continuous basis. Complete this specialization at your own pace.

This specialization consists of 4 courses:

SQL for Data Science
Data Wrangling, Analysis and AB Testing with SQL
Distributed Computing with Spark SQL
SQL for Data Science Capstone Project

Enrollments are accepted on a continuous basis. For more information on Coursera online courses, including enrollment policies and technical requirements, please visit: https://www.coursera.org/about/terms.

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Fee

Free and low-cost options available

Schedule

Enroll at any time and complete at your own pace.

Instructors

Katrina Glaeser

Katrina Glaeser received her Master’s degree in Mathematics from UC Davis, where she developed a love of teaching and was nominated for the Outstanding Graduate teaching award for her work on an online linear algebra course. Kat started her career working at Yammer which was responsible for introducing AB testing principles to the other parts of Microsoft’s Office team. Later she joined Pandora Media as part of a small team serving artists and the music industry. At Pandora, she developed the experiments, models, and methodology to help artists talk directly to their fans. Currently, Kat is part of a small team of data scientists at a Marco Polo, a video communication app that helps you feel close, even when life gets busy. Outside of the office she enjoys trail running with her dog, sending snail mail, and bike touring.

Conor Murphy

Conor Murphy lives at the intersection of data science and data engineering, driving data-driven decisions through distributed machine learning and inferential statistics. Currently he is a data scientist and machine learning subject matter expert at Databricks where he both teaches and consults. He transitioned to the tech sector after spending four years leveraging data for more impactful humanitarian interventions in developing countries with a focus on business development. He managed a multi-million dollar portfolio of grants for The Rotary Foundation focusing on developing and analyzing impact measurements in economic development initiatives, evaluating program participation and translating academic research into institution policies. He has held a variety of positions since his time in the nonprofit sector including a faculty role for Galvanize’s Data Science graduate program and principal data scientist and consultant for a number of startups. Outside of data, Conor is an avid skydiver who’s always looking for geeky ways to quantify his time in freefall.

Don Noxon

Don Noxon is a Research Data Scientist at Intel Corporation, where he has worked in many roles in his 22+ years with the company. Currently he is working on high-value business problems where they attempt to predict the future using Machine Learning and Deep Learning techniques; oftentimes needing to develop their own algorithms to be successful.

Sadie St. Lawrence

Sadie St. Lawrence is an AI Strategy Consultant for Accenture Applied Intelligence. Sadie brings a unique combination of technical expertise, analytics management experience and an ability to lead organizational change through compassion and problem-solving. She has trained over 70,000 people in Data Science and is an advocate for democratizing artificial intelligence and helping people transition into the 4th industrial revolution. In addition to her work with Accenture, Sadie is the Founder and CEO of Women in Data, a national non-profit organization focused on increasing diversity, creating connections, and driving meaning from data. Sadie is on a mission to bring compassion to business, and finds joy in helping individuals become liberated and find their own personal journey to a more authentic and connected life. In her free time, Sadie enjoys traveling, skiing, paddle boarding, yoga, and authentic conversations.