- Bash (Unix Shell)
- Database (DBMS)
- Web Application
- Python Programming
- SQL
- Vim
- Pandas
- Visual Studio Code
- Data Structure
- Data Management
- Linux
- Web Scraping
Python, Bash and SQL Essentials for Data Engineering 专项课程
Launch Your Career in Data Engineering. Master foundational strategies and tools to become proficient in developing data engineering and machine learning solutions
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您将学到的内容有
Develop data engineering solutions with a minimal and essential subset of the Python language and the Linux environment
Design scripts to connect and query a SQL database using Python
Use a scraping library in Python to read, identify and extract data from websites
Setup a provisioned Python project environment
您将获得的技能
关于此 专项课程
应用的学习项目
Each course includes integrated lab exercises using Visual Studio Code or Jupyter notebooks that give you an opportunity to practice the Python, Bash and SQL skills with real-world applications covered in each course. For each data engineering solution that you explore, you are also encouraged to create a demo video and GitHub repository of code that can be showcased in your digital portfolio for employers.By the end of this Specialization, you will have the foundational skills necessary to begin tackling more complex data engineering solutions.
Students should have beginner level Linux skills. No experience in Python is required.
Students should have beginner level Linux skills. No experience in Python is required.
专项课程的运作方式
加入课程
Coursera 专项课程是帮助您掌握一门技能的一系列课程。若要开始学习,请直接注册专项课程,或预览专项课程并选择您要首先开始学习的课程。当您订阅专项课程的部分课程时,您将自动订阅整个专项课程。您可以只完成一门课程,您可以随时暂停学习或结束订阅。访问您的学生面板,跟踪您的课程注册情况和进度。
实践项目
每个专项课程都包括实践项目。您需要成功完成这个(些)项目才能完成专项课程并获得证书。如果专项课程中包括单独的实践项目课程,则需要在开始之前完成其他所有课程。
获得证书
在结束每门课程并完成实践项目之后,您会获得一个证书,您可以向您的潜在雇主展示该证书并在您的职业社交网络中分享。

此专项课程包含 4 门课程
Python and Pandas for Data Engineering
In this first course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will learn how to set up a version-controlled Python working environment which can utilize third party libraries. You will learn to use Python and the powerful Pandas library for data analysis and manipulation. Additionally, you will also be introduced to Vim and Visual Studio Code, two popular tools for writing software. This course is valuable for beginning and intermediate students in order to begin transforming and manipulating data as a data engineer.
Linux and Bash for Data Engineering
In this second course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will learn the fundamentals of Linux necessary to perform data engineering tasks. Additionally, you will explore how to use both Bash and zsh configurations, and develop the syntax needed to interact and control Linux. These skills will allow you to manage and manipulate databases in a Bash environment.
Scripting with Python and SQL for Data Engineering
In this third course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will explore techniques to work effectively with Python and SQL. We will go through useful data structures in Python scripting and connect to databases like MySQL. Additionally, you will learn how to use a modern text editor to connect and run SQL queries against a real database, performing operations to load and extract data. Finally, you will use extracted data from websites using scraping techniques. These skills will allow you to work effectively when data is not readily available, or when spatial queries are required to extract useful information from databases.
Web Applications and Command-Line Tools for Data Engineering
In this fourth course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will build upon the data engineering concepts introduced in the first three courses to apply Python, Bash and SQL techniques in tackling real-world problems. First, we will dive deeper into leveraging Jupyter notebooks to create and deploy models for machine learning tasks. Then, we will explore how to use Python microservices to break up your data warehouse into small, portable solutions that can scale. Finally, you will build a powerful command-line tool to automate testing and quality control for publishing and sharing your tool with a data registry.
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杜克大学
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
常见问题
退款政策是如何规定的?
我可以只注册一门课程吗?
有助学金吗?
我可以免费学习课程吗?
此课程是 100% 在线学习吗?是否需要现场参加课程?
完成专项课程需要多长时间?
What background knowledge is necessary?
Do I need to take the courses in a specific order?
完成专项课程后我会获得大学学分吗?
What will I be able to do upon completing the Specialization?
Will I receive a transcript from Duke University for completing this course?
还有其他问题吗?请访问 学生帮助中心。