Disclosure: when you buy through links on our site, we may earn an affiliate commission.

Learn to code with an Introduction to Python 3

An introduction to Python 3 and interactive programming with Jupyter Notebooks
4.6
4.6/5
(105 reviews)
12,982 students
Created by

8.6

CourseMarks Score®

8.4

Freshness

8.2

Feedback

8.5

Content

Platform: Udemy
Video: 21h 46m
Language: English
Next start: On Demand

Table of contents

Description

This course is for beginners who are interested in learning to code. This course begins with teaching Python 3 in an interactive style through the use of Jupyter Notebooks. You will also learn to write programs within the integrated development environment (IDE) Pycharm.
In the setup videos for the course you will be told how to access the Github Repo which has all the content for the course additional to the videos hosted on Udemy. This additional content contains all the Python code files, the practice questions and solutions, as well as all the material in a nicely formatted online book.

Chapter 1: Intro To Python
•interactive Python
•Jupyter Notebooks
•print
•strings
•variables
•numerical data types (integers and floats)
•string formating with f-strings
•indexing and slicing strings
•getting input from a user
Chapter 2: Control Flow
•boolean data type (True and False)
•operators
•comparison operators (==, !=, >, <, >=, <=)
•logical operators (and, or, not)
•membership operators (in, not in)
•if, elif, and else statements
•lists
•indexing and slicing
•getting length of a list with len()
•appending to a list with append() and extend() methods
•list concatenation with + operator
•intro to mutable and immutable objects
•for loops and while loops
•range() function
•break and continue and pass statements
•more Python basic operators
•% modulus
•+=, -=, *=, /=
Chapter 3: Functions
•What are functions and why do we use them?
•Examples of functions that are built into Python.
•Defining your own functions.
•Function arguments
•positional arguments
•keyword arguments
•default arguments
•return statement
•Local and global scope
Chapter 4: Data Structures
•lists
•more list methods
•list comprehensions
•tuples
•dictionaries
•keys and values
•ways of iterating over dictionaries
•sets
•using *args and **kwargs in function definitions
Chapter 5: Virtual Environments, Packages, Pycharm IDE
•importing libraries in your Python code with import statements
•creating virtual environments for projects
•installing packages/libraries into those projects with pip
•creating your own modules for importing
•Setting up an integrated development environment (IDE) with the use of the popular IDE, Pycharm
Chapter 6: Truthy and Falsy Values, None Value, Exception Handling, Reading and Writing Files
•Truthy and Falsy values
•The None value
•About different Python errors and how to do exception handling with try and Except
•How to read data from a file and write data back to a file
Chapter 7: Intro to Classes and Object Oriented Programming
•defining and creating classes
•instantiate an object from a class
•instance methods and attributes
•class methods and attributes
•subclassing and inheritance

You will learn

✓ The basics of the python programming language.
✓ How to code.
✓ How to think critically and think like a programmer.
✓ How to write code and markdown in Jupyter Notebooks.
✓ Setting up Pycharm IDE and Virtual Environments
✓ Control Flow in Python
✓ Data Structures in Python
✓ Functions in Python
✓ Classes in Python

Requirements

• Basic computer knowledge
• Patience and willingness to learn.

This course is for

• Anyone looking for an introduction to coding.
• Anyone looking for an introduction to python programming language.
• Anyone looking for some foundations in Python so they can then look into more advanced topics after learning the basics.
Research Scientist / Data Scientist / PhD Applied Math
I left the world of academia for a career in data science. Through  years of industry experience I have developed skills as a full stack data scientist in the areas of data engineering, machine learning, data visualization, and productizing data science models. More recently I have been working as a research scientist with a focus on computer vision and deep learning.
I  have experience teaching thousands of students in mathematics at the university level as well as thousands of students on Udemy in areas like math, SQL, and coding. I  love to learn and teach others what I am learning.
I enjoy hanging out with my wife and three kids, playing guitar, playing basketball, biking, and learning.
Browse all courses by on Coursemarks.
Platform: Udemy
Video: 21h 46m
Language: English
Next start: On Demand

Students are also interested in