Guest Author: Matt Zand, President of High School Technology Services
Whether you are new to the field of data science or you would like to brush up on your current skills, the resources listed here would be a great help to you. For beginners, they should start by learning Python procedural coding followed by mastering Python Object-Oriented Programming (OOP). Python is a very powerful, yet easy to learn programming language. If you are familiar with the logic of programming, learning Python would be easy.
Once you master Python, you can move on to learning how to use Python for data analytics. Techniques and tools you use for running data analytics are common among data scientists that run analytics on large data sets (or so-called “Big Data”) on a daily basis.
The other two popular applications of Python are machine learning and Artificial Intelligence (AI). In short, by utilizing Python, machines will learn from their system and users and begin to replicate the business processes without any human interactions. Along similar lines, Python is used for AI by automating business processing and system routine transactions often via assistance from Internet of Things like hardware devices.
In short, the resources provided in this article can serve as great guides for those interested in pursuing a career in Data Science, Machine Learning, Big Data, Data Analytics, and AI.
Python, Machine Learning and Data Science Resources
- Python Basics
- Python OOP
- Python Data Analytics
- Python Database & Webapp
- Python Webapp with Flask
- Python IDEs & Tools
- Hands-on Machine Learning with Python
- Hands-on Data Science with Python
- Hands-on self-paced Python
- Learning Python and Python OOP
- Intro to Machine Learning with Python
- Intro to data science, data analytics and data visualizations with Python
- Introduction to Python Programming
- Learn Python OOP by Examples
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