In this practical, hands-on course you will learn how to program using python for data science, artificial intelligence and machine learning. This includes data analysis, visualization and how to make use of that data in a practical manner.
Video \content:
1. what is data types
2. what is string
3. strings in python
4. join strings
5. repeat strings
6. lowercase()
7. uppercase()
8. split()
9. join()
10. indexes
11. slicing
Our main objective is to give you the education not just to understand the ins and outs of the python programming language for data science, artificial intelligence and machine learning, but also to learn exactly how to become a professional Data Scientist with python and land your first job.
We will go over some of the best and most important python libraries for data science such as
Numpy, Pandas and Matplotlib +
• Numpy - A python library that makes a variety of mathematical and statistical operations easier. It is also the basis for many features of the pandas library.
• Pandas - A python library created specifically to facilitate working with data, this is the bread and butter of a lot of python data science work.
Numpy and Pandas are great for exploring and playing with data. Matplotlib is a data visualization library that makes graphs as you would find in excel or google sheets. Blending practical work with solid theoretical training, we take you from the basics of Python Programming for Data Science to mastery.
Python coding experience is either required or recommended in job posting for data scientists, machine learning engineers, big data engineers, IT specialists, database developers and much more.
Together we are going to give you the foundational education that you need to know not just on how to write code in python, analyze and visualize data and utilize machine learning algorithms but also how to get paid for your newly developed programming skills.
#data-types-in-python #strings-in-python #how-to-use-string-in-python
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