- Data Analysis
- Apache Spark
- Delta Lake
- SQL
- Data Science
- Sqlite
- A/B Testing
- Query String
- Predictive Analytics
- Presentation Skills
- creating metrics
- Exploratory Data Analysis
提供方
您將學到的內容有
Use SQL commands to filter, sort, & summarize data; manipulate strings, dates, & numerical data from different sources for analysis
Assess and create datasets to solve your business questions and problems using SQL
Use 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 present your findings & make recommendations
您將獲得的技能
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此專項課程包含 4 門課程
SQL for Data Science
As data collection has increased exponentially, so has the need for people skilled at using and interacting with data; to be able to think critically, and provide insights to make better decisions and optimize their businesses. This is a data scientist, “part mathematician, part computer scientist, and part trend spotter” (SAS Institute, Inc.). According to Glassdoor, being a data scientist is the best job in America; with a median base salary of $110,000 and thousands of job openings at a time. The skills necessary to be a good data scientist include being able to retrieve and work with data, and to do that you need to be well versed in SQL, the standard language for communicating with database systems.
Data Wrangling, Analysis and AB Testing with SQL
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. We'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.
Distributed Computing with Spark SQL
This course is all about big data. It’s for students with SQL experience that want to take the next step on their data journey by learning distributed computing using Apache Spark. Students will gain a thorough understanding of this open-source standard for working with large datasets. Students will gain an understanding of the fundamentals of data analysis using SQL on Spark, setting the foundation for how to combine data with advanced analytics at scale and in production environments. The four modules build on one another and by the end of the course you will understand: the Spark architecture, queries within Spark, common ways to optimize Spark SQL, and how to build reliable data pipelines.
SQL for Data Science Capstone Project
Data science is a dynamic and growing career field that demands knowledge and skills-based in SQL to be successful. This course is designed to provide you with a solid foundation in applying SQL skills to analyze data and solve real business problems.
提供方

加州大学戴维斯分校
UC Davis, one of the nation’s top-ranked research universities, is a global leader in agriculture, veterinary medicine, sustainability, environmental and biological sciences, and technology. With four colleges and six professional schools, UC Davis and its students and alumni are known for their academic excellence, meaningful public service and profound international impact.
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