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Python Fundamentals for Data Science

Python Fundamentals for Data Science
Python Fundamentals for Data Science
Created by Saima Aziz | Published 12/2020
Duration: 2.5 hours | 4 sections | 29 lectures | Video: 1280x720, 44 KHz | 1.4 GB
Genre: eLearning | Language: English + Sub
Python for Data Science Students


Python Fundamentals for Data Science


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What you'll learn
The student will cover the following fundamentals of programming concepts using Jupiter notebook.
Addressing a string index
Negative Index
Access sub-strings
Access start of sub-strings
Access end of sub-strings
Access sub-strings by step size
Accessing sub-strings stepping backwards
Iterate a string: for in statement
Iterate by sub-string
String Methods len()
String Methods count()
String Methods find()
Creating Lists
Accessing Lists by using Index
Insert a new value for an index
Appending to a list
Insert Items into a list
Delete a specific list index
Empty list is false
Delete a specific object from a list with .remove()
Enumerate function etc
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Requirements
Introduction to Python: For absolute beginners by Saima AzizLaptop or PC with Internet ConnectionMotivation to learn
Description
Welcome to Fundamentals of Python. My name is Saima Aziz and I will be the instructor for this course.
Python is a general purpose and high level programming language. You can use Python for developing desktop GUI applications, websites and web applications. Python is a high level programming language. It allows you to focus on core functionality of the application by taking care of common programming tasks.
By taking this course, you have entered into an exciting world of self-paced, online learning! If online education is new to you, don't worry!
I have carefully designed the content of the course to be comprehensive and fully compatible with industrial requirements and easy to understand.
Each section will generally have some video content, reading material, problem sets, and a set of assessment questions to test your knowledge.
We will use Jupiter Notebook where samples can be run, and where practice tasks and code quizzes can be completed.
I encourage you to take the course from beginning to end to get the full learning experience. Some sections may be very easy for you and others will be challenging, but each section should offer something of value. There's nothing like that feeling of accomplishment when you complete something from beginning to end, so hang in there, and enjoy the course!
If you get stuck, don't give up! There is enough material in the sections to help you solve the problems and your hard work will pay off.
Who this course is for:Beginners, who want to learn fundamentals of Python from Scratch, curios about data science

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Python Fundamentals for Data Science

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