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Python Learning Resources Table_v3
Here's a comprehensive guide to each of the topics you've requested:
Python offers a rich ecosystem of libraries for creating various types of data visualizations. Here are some of the most popular ones:
Library Name | Description | Usage/Strength | License | Documentation |
---|---|---|---|---|
Matplotlib | 2D plotting library for static, animated, and interactive visualizations. | Suitable for creating publication-quality charts, low-level control. | PSF License | Matplotlib Docs |
Seaborn | Built on top of Matplotlib, it simplifies the creation of beautiful statistical plots. | Ideal for statistical visualization and complex data relationships. | BSD License | Seaborn Docs |
Plotly | Interactive plotting library with support for web-based visualizations (dashboards). | Best for interactive plots and dashboards with real-time data. | MIT License | Plotly Docs |
Bokeh | Allows for interactive visualizations that are web-ready. | Best for real-time web apps and highly interactive plots. | BSD License | Bokeh Docs |
Altair | Declarative statistical visualization library based on Vega and Vega-Lite grammars. | High-level and ideal for statistical charts with less code. | BSD License | Altair Docs |
ggplot | Python port of the popular R library ggplot2. | Good for those familiar with ggplot2 syntax from R, works well with data frames. | BSD License | ggplot GitHub |
The following courses cover machine learning concepts with Python, ideal for beginners and advanced learners alike:
Course Name | Free | Level | Topics Covered | Certification | Platform | Duration |
---|---|---|---|---|---|---|
Andrew Ng’s Machine Learning with Python | Yes | Beginner to Intermediate | Linear Regression, Neural Networks, SVM, Unsupervised Learning | Verified Certificate (Paid) | Coursera | 60+ hours |
DataCamp’s Machine Learning Scientist Track | No | Intermediate to Advanced | Supervised, Unsupervised Learning, Feature Engineering, Deep Learning | DataCamp Career Track Badge | DataCamp | Varies (10+ courses) |
fast.ai’s Practical Deep Learning for Coders | Yes | Intermediate to Advanced | Deep Learning, Neural Networks, CNNs, Transfer Learning | No | fast.ai | 7 weeks |
Google’s Machine Learning Crash Course | Yes | Beginner | Intro to Machine Learning, TensorFlow, Supervised Learning | No | 15 hours | |
IBM AI Engineering Professional Certificate | No | Intermediate | Machine Learning, Deep Learning, AI models, Neural Networks | Professional Certificate | Coursera (IBM) | 6 months |
Automation tools written in Python can save time and reduce errors in repetitive tasks. Here's a list of Python automation tools for business purposes:
Tool/Library | Description | Use Cases | License | Documentation |
---|---|---|---|---|
Selenium | Browser automation for testing or automating web tasks. | Web scraping, web app testing, form filling, browser automation | Apache 2.0 License | Selenium Docs |
PyAutoGUI | Allows you to control mouse and keyboard programmatically. | GUI automation, repetitive form filling, automating mouse clicks | BSD License | PyAutoGUI Docs |
AutoPy | Another library for controlling the keyboard and mouse, plus capturing screenshots. | UI automation, data entry | MIT License | AutoPy GitHub |
Pandas | Data manipulation and analysis library that can be used to automate tasks like data cleaning. | Automating data processing tasks, handling Excel files | BSD License | Pandas Docs |
OpenPyXL | A library for reading and writing Excel files. | Automating Excel report generation, data extraction | MIT License | OpenPyXL Docs |
Requests | HTTP library for automating interaction with web services. | Automating web API requests, downloading files | Apache 2.0 License | Requests Docs |
Although Python is not typically associated with mobile app development, there are several frameworks that allow you to build mobile apps using Python:
Framework | Description | Platform | License | Documentation |
---|---|---|---|---|
Kivy | Open-source Python library for rapid development of cross-platform applications (Android, iOS, etc.). | Android, iOS | MIT License | Kivy Docs |
BeeWare | A collection of tools and libraries for building native apps on various platforms using Python. | Android, iOS, macOS | BSD License | BeeWare Docs |
PyQt | Python bindings for the Qt framework, allowing for the creation of cross-platform GUI applications. | Android, iOS | GPL/LGPL License | PyQt Docs |
Toga | Part of the BeeWare project, this library allows for native mobile apps with a Python backend. | Android, iOS | BSD License | Toga Docs |
SL4A (Scripting Layer for Android) | A project that enables writing Android apps using Python scripts. | Android | Apache 2.0 License | SL4A GitHub |
Python certification programs provide structured learning paths and a way to validate your skills. Here are some popular options:
Certification Program | Cost | Level | Certification Body | Topics Covered | Duration |
---|---|---|---|---|---|
Python Institute’s PCAP Certification | $295 | Intermediate | Python Institute | Python Basics, OOP, File Operations, Exceptions Handling, Libraries | Self-paced |
Microsoft Certified: Python Developer | $165 | Intermediate | Microsoft | Python Programming, Data Analysis, Web Development | Varies |
Google IT Automation with Python | $39/month | Beginner to Intermediate | Google/Coursera | Automation, Python Scripts, Troubleshooting, System Management | 6 months |
**[edX Professional Certificate in Python for Data Science](https://www.edx.org/pro | |||||
fessional-certificate/python-for-data-science)** | Varies | Intermediate | IBM/edX | Python, Pandas, Numpy, Matplotlib, Data Visualization, Machine Learning | 5-7 weeks |
Udemy Python Certification Course | $19.99+ | Beginner | Udemy | Python Basics, Data Structures, Automation, Web Scraping | 20+ hours |
I hope this guide helps you explore each of these key topics! Let me know which section you'd like to dive into or if you need further assistance on a specific resource.
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