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.
Web Applications and Command-Line Tools for Data Engineering
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Web Applications and Command-Line Tools for Data Engineering
This course is part of Python, Bash and SQL Essentials for Data Engineering Specialization
Instructors: Noah Gift
4,224 already enrolled
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Gain insight into a topic and learn the fundamentals.
4.3
(35 reviews)
Intermediate level
Recommended experience
43 hours to complete
3 weeks at 14 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Construct Python Microservices with FastAPI
Build a Command-Line Tool in Python using Click
Compare multiple ways to set up and use a Jupyter notebook
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
17 assignments
Taught in English
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This course is part of the Python, Bash and SQL Essentials for Data Engineering Specialization
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There are 4 modules in this course
In this module, you will learn how to install and run Jupyter on your local machine. Additionally, you will explore strategies to use code and text cells in a Jupyter notebook.
What's included
8 videos4 readings1 assignment1 discussion prompt3 ungraded labs
In this module, you will learn how to create and use a Cloud-based notebook in Google Colab and AWS Sagemaker.
What's included
6 videos4 readings7 assignments1 ungraded lab
In this module, you will learn how to build a Python Microservice with FastAPI and deploy a containerized machine learning Microservice for data engineering.
What's included
11 videos7 readings4 assignments1 ungraded lab
In this module, you will learn how to organize a Python project so you can build a powerful command-line tool. You will use Click, a useful command-line tool framework to enhance your tool. Finally, you will automate testing and quality control for publishing and sharing your tool with a registry.
What's included
25 videos11 readings5 assignments5 ungraded labs
Offered by
Recommended if you're interested in Data Management
Duke University
Duke University
Duke University
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4.3
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Reviewed on Feb 14, 2023
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