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INE - Regular Expressions With Python [FCO]
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INE - Regular Expressions With Python [FCO]

About Course

This course will explain the relevance of regexes in programming, cover their history and background, explain the fundamentals of regexes in Python, including Match objects, searching, groups, etc. and explain variations like compilation flags and performance considerations.

Nail Your Next Project

Take your technical training into your own hands and stay engaged with our learn-by-doing platform where you can put your skills to the test with hands-on exercises, quizzes, and labs.

Instructor(s)

David is the founder of KDM Training, an organization dedicated to educating developers and data scientists in machine learning and scientific computing. His training experience also includes creating the data science training program for Anaconda Inc. where he was a senior trainer. In addition, he was honored to work for eight years with D.E. Shaw Research, who built the world's fastest, highly-specialized (down to the ASICs and network layer), supercomputer for performing molecular dynamics.

David is heavily involved in the Data Science community and served as Director of the PSF for six years, and remains co-chair of its Trademarks Committee and of its Scientific Python Working Group. His columns, Charming Python and XML Matters, written in the 2000s, were the most widely read articles in the Python world. He has also written previous books for Packt, O'Reilly and Addison-Wesley, and has given keynote addresses at numerous international programming conferences.

David received his Ph.D. in Philosophy as well as a Master of Arts in Philosophy and a Bachelor of Arts in Photography and Mathematics.

General Info:

Author(s): David Mertz
Language: English
Updated: 12/2022
Videos Duration: 4h
Course Source: https://ine.com/learning/courses/regular-expressions-with-python

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1. Course Introduction.mp47.36 MiB
1. Course Introduction.mp4.jpg168.13 KiB
2. Why Regular Expressions.mp451.13 MiB
3. Groups and Classes.mp457.69 MiB
4. Lookahead and Lookbehind.mp446.78 MiB
5. Python Functions.mp456.47 MiB
6. Flags and Performance.mp448.96 MiB
7. Course Conclusion.mp47.21 MiB
Course data.zip1.63 KiB
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