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Validate Data Classes with Pydantic

Sarah Holderness

In this short demo, Sarah Holderness will show you how to validate data classes with pydantic.

In this short demo, Sarah Holderness will show you how to validate data classes with pydantic.

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What's inside

Syllabus

Validate Data Classes with Pydantic

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Validates data classes with Pydantic, which is a lightweight library that supports type annotation features
Taught by Sarah Holderness, who's an experienced instructor in data validation and software development
Short and to-the-point, suitable for learners who want a quick introduction to the topic

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Activities

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Career center

Learners who complete Validate Data Classes with Pydantic will develop knowledge and skills that may be useful to these careers:
Data Scientist
A Data Scientist uses data to build predictive models and solve business problems. This course on validating data classes with Pydantic may be useful for those looking to enter this field, as it provides a foundation in data validation techniques that are essential for ensuring the accuracy and reliability of data models.
Machine Learning Engineer
A Machine Learning Engineer builds and deploys machine learning models. This course on validating data classes with Pydantic may be useful for those looking to enter this field, as it provides a foundation in data validation techniques that are essential for ensuring the accuracy and reliability of machine learning models.
Business Analyst
A Business Analyst analyzes business processes and helps businesses improve their efficiency and effectiveness. This course on validating data classes with Pydantic may be useful for those looking to enter this field, as it provides a foundation in data validation techniques that are essential for ensuring the accuracy and reliability of data used in business analysis.
Statistician
A Statistician collects, analyzes, and interprets data to help businesses make informed decisions. This course on validating data classes with Pydantic may be useful for those looking to enter this field, as it provides a foundation in data validation techniques that are essential for ensuring the accuracy and reliability of data used in statistical analysis.
Data Architect
A Data Architect designs and manages data systems. This course on validating data classes with Pydantic may be useful for those looking to enter this field, as it provides a foundation in data validation techniques that are essential for ensuring the integrity of data systems.
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course on validating data classes with Pydantic may be useful for those looking to enter this field, as it provides a foundation in data validation techniques that are essential for ensuring the accuracy and reliability of software applications.
Data Analyst
A Data Analyst gathers, cleans, and interprets data to help businesses make informed decisions. This course on validating data classes with Pydantic may be useful for those looking to enter this field, as it provides a foundation in data validation techniques that are essential for ensuring the accuracy and reliability of data analysis.
Database Administrator
A Database Administrator designs, implements, and maintains databases. This course on validating data classes with Pydantic may be useful for those looking to enter this field, as it provides a foundation in data validation techniques that are essential for ensuring the accuracy and reliability of data stored in databases.
Information Security Analyst
An Information Security Analyst protects data from unauthorized access, use, disclosure, disruption, modification, or destruction. This course on validating data classes with Pydantic may be useful for those looking to enter this field, as it provides a foundation in data validation techniques that are essential for ensuring the accuracy and reliability of data used in information security analysis.
Financial Analyst
A Financial Analyst analyzes financial data to help businesses make informed decisions. This course on validating data classes with Pydantic may be useful for those looking to enter this field, as it provides a foundation in data validation techniques that are essential for ensuring the accuracy and reliability of financial data.
Risk Analyst
A Risk Analyst identifies and manages risks to businesses. This course on validating data classes with Pydantic may be useful for those looking to enter this field, as it provides a foundation in data validation techniques that are essential for ensuring the accuracy and reliability of data used in risk analysis.
Data Engineer
A Data Engineer designs, builds, and maintains data pipelines and systems. This course on validating data classes with Pydantic may be useful for those looking to enter this field, as it provides a foundation in data validation techniques that are essential for ensuring the integrity of data pipelines.
Auditor
An Auditor examines financial records to ensure that they are accurate and complete. This course on validating data classes with Pydantic may be useful for those looking to enter this field, as it provides a foundation in data validation techniques that are essential for ensuring the accuracy and reliability of financial data.
Compliance Analyst
A Compliance Analyst ensures that businesses comply with laws and regulations. This course on validating data classes with Pydantic may be useful for those looking to enter this field, as it provides a foundation in data validation techniques that are essential for ensuring the accuracy and reliability of data used in compliance analysis.
Data Governance Officer
A Data Governance Officer ensures that data is used in a consistent and ethical manner. This course on validating data classes with Pydantic may be useful for those looking to enter this field, as it provides a foundation in data validation techniques that are essential for ensuring the accuracy and reliability of data used in data governance.

Reading list

We've selected ten books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Validate Data Classes with Pydantic.
Provides a comprehensive overview of reinforcement learning with Python, including coverage of data validation with Pydantic. It great resource for anyone who wants to learn more about reinforcement learning with Python.
Provides a comprehensive overview of machine learning with Python, including coverage of data validation with Pydantic. It great resource for anyone who wants to learn more about machine learning with Python.
Provides a comprehensive overview of deep learning with Python, including coverage of data validation with Pydantic. It great resource for anyone who wants to learn more about deep learning with Python.
Provides a comprehensive overview of natural language processing with Python, including coverage of data validation with Pydantic. It great resource for anyone who wants to learn more about natural language processing with Python.
Provides a comprehensive overview of computer vision with Python, including coverage of data validation with Pydantic. It great resource for anyone who wants to learn more about computer vision with Python.
Provides a comprehensive overview of data science with Python, including coverage of data validation with Pydantic. It great resource for anyone who wants to learn more about data science with Python.
Provides a comprehensive overview of Flask, a popular Python web framework. It covers a range of topics, including data validation with Pydantic. It great resource for anyone who wants to learn how to build web applications with Flask.
Provides a collection of recipes for data manipulation tasks in Python. It covers topics such as data cleaning, normalization, and validation.
Provides a practical guide to data validation techniques. It covers topics such as data cleaning, normalization, and validation.
Provides a comprehensive guide to data quality and data validation techniques. It covers topics such as data cleaning, normalization, and validation.

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