Python: Python Basics Bootcamp for Beginners in Data Science
Python: Python Basics Bootcamp for Beginners in Data Science, available at $19.99, has an average rating of 3.85, with 59 lectures, based on 92 reviews, and has 10981 subscribers.
You will learn about Python Basics Python Lists Python Dictionaries While Loops For Loops Python Functions This course is ideal for individuals who are Beginners or Enthusiasts It is particularly useful for Beginners or Enthusiasts.
Enroll now: Python: Python Basics Bootcamp for Beginners in Data Science
Summary
Title: Python: Python Basics Bootcamp for Beginners in Data Science
Price: $19.99
Average Rating: 3.85
Number of Lectures: 59
Number of Published Lectures: 59
Number of Curriculum Items: 59
Number of Published Curriculum Objects: 59
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Python Basics
- Python Lists
- Python Dictionaries
- While Loops
- For Loops
- Python Functions
Who Should Attend
- Beginners
- Enthusiasts
Target Audiences
- Beginners
- Enthusiasts
Beginner Friendly: Learning python for data science the right way.
As a beginner when learning python for data analysis or data science you do it differently from someone learning it to be a developer ( web, apps or games). Content in this course is designed to fast track you to the next stage by teaching you the relevant topics that will help you get started in the next python libraries for data analysis & data science. These libraries include NumPy, pandas and sci-kit learn.
Practice-based learning
The best way to remember when learning is to learn by doing. In each section, you learn the theory behind then we deep-dive into practice. The tutorials are designed so that you follow on your own computer in tackling small practice examples.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Lecture 2: Tips
Lecture 3: What is programming
Lecture 4: Print Function
Lecture 5: Print Practice
Chapter 2: Pyton Variables
Lecture 1: Variables intro
Lecture 2: variables practice
Lecture 3: to note
Lecture 4: python syntax
Lecture 5: variable data types
Chapter 3: Numeric Data Type
Lecture 1: intro
Lecture 2: numeric operators
Lecture 3: numeric data type practice
Chapter 4: String Data Types
Lecture 1: intro
Lecture 2: intro 2
Lecture 3: indexing strings
Lecture 4: indexing practice
Lecture 5: slicing strings
Lecture 6: slicing strings practice
Lecture 7: string methods
Lecture 8: string methods practice
Chapter 5: Python Lists
Lecture 1: intro
Lecture 2: indexing lists
Lecture 3: indexing practice
Lecture 4: slicing lists
Lecture 5: slicing lists practice
Lecture 6: nested lists
Lecture 7: nested lists practice
Lecture 8: list methods
Lecture 9: list methods 2
Lecture 10: list methods practice
Lecture 11: tuples
Lecture 12: diffrenece between lists & tuples
Chapter 6: Python Dictionary
Lecture 1: intro
Lecture 2: dictionary practice
Lecture 3: dictionary practice 2
Lecture 4: dictionary methods
Chapter 7: Python Functions
Lecture 1: intro
Lecture 2: functions practice
Lecture 3: function parameters
Lecture 4: parameters practice
Lecture 5: keyword arguments
Lecture 6: keyword argumennts practice
Lecture 7: default arguments
Lecture 8: print & return
Chapter 8: Conditionals ( IF , ELIF & ELSE )
Lecture 1: intro
Lecture 2: if statements
Lecture 3: else statements
Lecture 4: elif statements
Lecture 5: elif statements
Lecture 6: fyi
Chapter 9: Python Loops ( While & For Loops)
Lecture 1: while loops
Lecture 2: for loops
Lecture 3: for loops practice
Lecture 4: for loops practice 2
Lecture 5: for loops practice
Lecture 6: statements
Lecture 7: break statement practice
Lecture 8: continue statements practice
Instructors
-
Shepherd Mahupa
Data Scientist
Rating Distribution
- 1 stars: 3 votes
- 2 stars: 5 votes
- 3 stars: 21 votes
- 4 stars: 31 votes
- 5 stars: 32 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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