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所在平台: Udemy |
课程主页: https://www.udemy.com/course/become-an-sql-data-engineerdata-analyst/
课程评论：没有评论
课程名称：成为SQL数据工程师/数据分析师 课程概述：SQL数据工程师/数据分析师课程是一项全面的学习体验，旨在培养学生在现实数据工程和数据分析场景中运用SQL强大功能的技能。本课程深入探讨SQL，从基础到高级概念，包括NoSQL、大数据技术和数据可视化等重要主题。 课程开始时，学生将了解数据分析师和数据工程师的角色与职责，强调SQL在这些职业中的重要性。学生将熟悉多种SQL数据库，如MS SQL、MySQL、PostgreSQL和Oracle SQL。接下来，逐步学习SQL基础知识，包括语法、数据类型、运算符、表达式及常用的SQL语句以操作数据库中的数据。 之后，课程将深入更复杂的SQL概念，如函数、连接（joins）、子查询、视图、索引和约束。学生有机会掌握编写复杂SQL查询的艺术，并有效管理数据库，包括学习必要的数据清洗技术，理解数据的导入与导出，以及数据库的备份与恢复。 课程特别强调使用SQL进行数据分析，涵盖描述性统计、分组（group by）、having与order by子句、窗口函数和其他在数据分析中使用的高级SQL技巧。同时，课程也探讨了使用SQL进行数据工程任务，如设计数据库、处理ETL流程及管理大规模数据集。 此外，课程还探索了NoSQL数据库中的SQL类查询，帮助学生对数据生态系统有更广泛的理解。它介绍了Hadoop和Spark等大数据技术，并展示SQL如何与这些工具相结合。由于可视化在数据分析中至关重要，课程讲解了如何将SQL与流行的数据可视化工具如Tableau和PowerBI结合使用。 最后，学生将学习SQL最佳实践和性能优化策略，确保编写的SQL查询不仅功能正常，还高效和安全。课程的高潮是一项总结项目，允许学生将所学知识和技能应用于真实数据问题，展示他们在数据工程和数据分析中使用SQL的能力。 本课程为希望提升数据分析和数据工程领域技能的任何人提供，结合理论课程、实践练习和测验，帮助学生获得实际操作经验和深入的SQL知识，使他们能够在职业生涯中取得成功。
The SQL Data Engineer/Data Analyst course is a comprehensive learning experience that equips students with the skills to leverage SQL's powerful features in real-world data engineering and data analysis scenarios. This course offers an in-depth exploration of SQL, extending from the basics to advanced concepts, and including essential topics like NoSQL, Big Data technologies, and data visualization.This course begins by introducing students to the roles and responsibilities of data analysts and data engineers, emphasizing the significance of SQL in these professions. It familiarizes students with a variety of SQL databases such as MS SQL, MySQL, PostgreSQL, and Oracle SQL. Gradually, we delve into the fundamentals of SQL, including its syntax, data types, operators, and expressions, and the common SQL statements used to manipulate data in databases.We then advance to more complex SQL concepts like functions, joins, subqueries, views, indexes, and constraints. Students will have an opportunity to master the art of writing sophisticated SQL queries, and manage databases effectively. This includes learning essential data cleaning techniques and understanding the import and export of data, as well as backup and restoration of databases.The course also places a special focus on using SQL for data analysis. It covers topics like descriptive statistics, group by, having and order by clauses, window functions, and other advanced SQL techniques used in data analysis. Simultaneously, it sheds light on using SQL for data engineering tasks, such as designing databases, handling ETL processes, and managing large datasets.Moreover, the curriculum explores SQL-like queries in NoSQL databases, helping students gain a broader understanding of the data ecosystem. It provides an introduction to Big Data technologies like Hadoop and Spark and shows how SQL interfaces with these tools. As visualization is crucial in data analysis, the course outlines how to use SQL with popular data visualization tools like Tableau and PowerBI.Finally, students learn SQL best practices and performance optimization strategies, ensuring that they not only write functional SQL queries but also write efficient and secure ones.The culmination of the course is a capstone project, which allows students to apply their acquired knowledge and skills to a real-world data problem, demonstrating their proficiency in using SQL for data engineering and data analysis.This course is designed for anyone looking to upskill in the field of data analysis and data engineering. With a blend of theoretical lessons, practical exercises, and quizzes, students will gain hands-on experience and in-depth knowledge of SQL, enabling them to succeed in their professional careers.
