Download Python A-Z™: Python For Data Science With Real Exercises! udemy course and learn Programming In Python For Data Analytics And Data Science. Learn Statistical Analysis, Data Mining And Visualization
What you’ll learn
- Learn to program in Python at a good level
- Learn how to code in Jupiter Notebooks
- Learn the core principles of programming
- Learn how to create variables
- Learn about integer, float, logical, string and other types in Python
- Learn how to create a while() loop and a for() loop in Python
- Learn how to install packages in Python
- Understand the Law of Large Numbers
- No prior knowledge or experience needed. Only a passion to be successful!
Learn Python Programming by doing!
There are bunches of Python courses and addresses out there. In any case, Python has a lofty expectation to absorb information and understudies frequently get overpowered. This course is unique!
This course is genuinely well ordered. In each new instructional exercise we expand on what had officially realized and push one additional progression ahead.
After each video you gain proficiency with another significant idea that you can apply immediately. What’s more, best of all, you learn through live models.
This preparation is pressed with genuine logical difficulties which you will figure out how to unravel. A portion of these we will tackle together, some you will have as homework works out.
In synopsis, this course has been intended for all expertise levels and regardless of whether you have no programming or measurable foundation you will be effective in this course!
Who this course is for:
- This course if for you if you want to learn how to program in Python
- This course is for you if you are tired of Python courses that are too complicated
- This course is for you if you want to learn Python by doing
- This course is for you if you like exciting challenges
- You WILL have homework in this course so you have to be prepared to work on it
Created by Kirill Eremenko, SuperDataScience Team
Last updated 4/2019
Size: 2.14 GB