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220922 ||| eng |
| 050 |
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4 |
|a QA76.73.P98
|
| 100 |
1 |
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|a Deza, Alfredo
|e presnter
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| 245 |
0 |
0 |
|a Python bootcamp for data
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| 250 |
|
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|a [First edition]
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| 260 |
|
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|a [Place of publication not identified]
|b Pragmatic AI Solutions
|c 2022
|
| 300 |
|
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|a 1 video file (4 hr., 10 min.)
|b sound, color
|
| 653 |
|
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|a Computer programming / fast
|
| 653 |
|
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|a Python (Computer program language) / fast
|
| 653 |
|
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|a Python (Computer program language) / http://id.loc.gov/authorities/subjects/sh96008834
|
| 653 |
|
|
|a Programmation (Informatique)
|
| 653 |
|
|
|a Computer programming / http://id.loc.gov/authorities/subjects/sh85107310
|
| 653 |
|
|
|a Python (Langage de programmation)
|
| 653 |
|
|
|a computer programming / aat
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b OREILLY
|a O'Reilly
|
| 856 |
4 |
0 |
|u https://learning.oreilly.com/videos/~/50146VIDEOPAIML/?ar
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 005.13/3
|
| 520 |
|
|
|a Learn Objectives This course has extensive content that covers Python for beginners and then moves onto more complex Python operations including data analysis, exploration, and manipulation with Pandas and NumPy.
|
| 520 |
|
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|a It will include the following learning objectives: Work with logic in Python, assigning variables and using different data structures Create functions and classes of different types Write, run, and debug tests using Pytest to validate your work Manipulate data with Pandas Create and modify NumPy arrays Index This course is divided into content for 4 weeks,
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| 520 |
|
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|a Python Bootcamp for Data Learn foundational Python with an emphasis for data In this course, you will learn how to work effectively with Python. You will understand how to use variables, create functions, and work with classes. That foundational knowledge will allow you to understand testing and testing techniques to validate your work and then move onto Pandas and Numpy which allows you to work effectively with data sets and other data science tasks. This is valuable for anyone wanting to get a quick introductory course on Python, like a student, programmer new to Python or aspiring data engineer or data scientist. At the end of this course you'll be ready to work with more advanced concepts with Pandas and Numpy with a solid foundation in Python for any other task. All lessons and videos have accompanying GitHub Repositories with example code.
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| 520 |
|
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|a with 3 lessons per week: Week 1: Introduction to Python Reference GitHub Repository Working with variables and types Introduction to Python data structures Adding and extracting data from data structures Week 2: Python functions and Classes Reference GitHub Repository Working with functions Building classes and using methods Modules and advanced usage Week 3: Testing in Python Reference GitHub Repository Introduction to testing Writing useful tests Test failures Week 4: Introduction to Pandas and Numpy Reference GitHub Repository Basic Pandas usage Working with datasets Introduction to NumPy Resources Week 1 GitHub repository: Introduction to Python Week 2 GitHub repository: Python Functions and Classes Week 3 GitHub repository: Testing In Python Week 4 GitHub repository: Introduction to Pandas and Numpy Python dictionaries Learn Module Testing In Python book Minimal Python book Python for Beginners Learn Path Practical MLOps book
|