Python 3: Fundamentals
Python 3: Fundamentals, available at $94.99, has an average rating of 4.7, with 286 lectures, based on 2292 reviews, and has 15844 subscribers.
You will learn about Learn Python fundamentals Basic to advanced data types Functional and Object Oriented programming Closures and decorators Datetime and timezone handling Reading and writing text, CSV and JSON files Making REST API requests Fundamentals of NumPy Fundamentals of Pandas Fundamentals of Matplotlib This course is ideal for individuals who are Beginners who want to learn Python like a software engineer or Students who want to gain a solid fundamental understanding of the Python language and ecosystem or Software engineers with knowledge of other languages, but new to Python or Not intended for students looking for a "quick and light" introduction to Python It is particularly useful for Beginners who want to learn Python like a software engineer or Students who want to gain a solid fundamental understanding of the Python language and ecosystem or Software engineers with knowledge of other languages, but new to Python or Not intended for students looking for a "quick and light" introduction to Python.
Enroll now: Python 3: Fundamentals
Summary
Title: Python 3: Fundamentals
Price: $94.99
Average Rating: 4.7
Number of Lectures: 286
Number of Published Lectures: 286
Number of Curriculum Items: 286
Number of Published Curriculum Objects: 286
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn Python fundamentals
- Basic to advanced data types
- Functional and Object Oriented programming
- Closures and decorators
- Datetime and timezone handling
- Reading and writing text, CSV and JSON files
- Making REST API requests
- Fundamentals of NumPy
- Fundamentals of Pandas
- Fundamentals of Matplotlib
Who Should Attend
- Beginners who want to learn Python like a software engineer
- Students who want to gain a solid fundamental understanding of the Python language and ecosystem
- Software engineers with knowledge of other languages, but new to Python
- Not intended for students looking for a "quick and light" introduction to Python
Target Audiences
- Beginners who want to learn Python like a software engineer
- Students who want to gain a solid fundamental understanding of the Python language and ecosystem
- Software engineers with knowledge of other languages, but new to Python
- Not intended for students looking for a "quick and light" introduction to Python
This Course in a Nutshell
Aimed at beginner Python developers, this course will provide you a fundamental understanding of how to program in Python. Your journey will take you from a total Python beginner to an intermediate level Python developer more than ready to tackle your own professional projects.
Although not technically required, limited prior experience in any coding language, and a basic understanding of concepts such as looping, branching, etc will prove useful.
This course will provide you the solid foundation you will need to continue moving forward in your Python development endeavors. This course is not a “here’s how I do it, just type along please” type of course – its goal is to make you understand each and every line of code we are going to write together, why we write it and why it works, giving you the knowledge to apply the same coding techniques to your own situation and problems.
Like any good college level course, this course is fairly lengthy and will require time, not only for watching the videos, but also working on your own to explore the various topics, trying things out, and at the end of each section working on increasingly complex problems. It takes a certain amount of time to master a programming language, and this course is no exception. If you are looking for a quick and superficial intro to Python, then this course is probably not for you.
VERY IMPORTANT: Before attempting this course you must have a basic knowledge of how to use the DOS prompt (Windows) or shell (Linux/Mac). This means how to open a prompt/shell on your computer, navigating the file structure using cd, creating and deleting directories, copying files/directories from one location to another, listing files in the current directory, etc. There are plenty of 20-30 minute tutorials available online that will teach you those simple basics.
Course Overview
This course balances theory and coding practice. Most subjects are two-part: a theory (or lecture) video where we cover a specific topic, explain how things work, followed by a practice (or coding) video which takes the lecture material and applies it using real code. I highly encourage you to take notes during the lectures, and code along with me during the coding videos – that’s the beauty of online videos – you can pause, rewind, speed up, slow down as you need!
All the course slides (over 900 of them!) are available for download if you prefer that approach over taking your own notes – however I recommend you take your own notes, preferably after watching the corresponding code video – you’ll remember things better that way!
We use Jupyter notebooks as the perfect tool for teaching and learning Python.
Jupyter notebooks support both Python code as well as interspersed markdown documentation. You will find that every code video in this course has a corresponding Jupyter notebook available in the course downloads, that not only reproduces all the code we do in the coding videos, but is fully annotated with explanations of the code, basically what I cover in the coding videos, and sometimes more!
All the notebooks and the data files we will work with, are available in the course downloads in the first section of this course as well as in GitHub.
At the end of each section, you will find a set of exercises with solutions. It is imperative that you work through these exercises, and only move on to the next section once you are able to do these exercises on your own. Each section of this course builds on top of the previous one!
The course is broadly broken down into three main parts:
Python Basics
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What is Python
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How to install Python
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How to create and use virtual environments
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How to run Python and Jupyter notebooks
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Basic data types including integers, floats, booleans
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Boolean operators
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Arithmetic and comparison operators, as well as operator precedence
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Conditional execution
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Looping (for and while)
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Sequence types such as lists, tuples and strings
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Working with sequence types (iterating, slicing, manipulating, copying, unpacking)
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More on strings and Unicode
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Dictionaries and sets
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Python’s list, dictionary and set comprehensions
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Exceptions and exception handling
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Iterables and iterators, including generators
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Writing user defined functions and different ways of defining and passing arguments
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Lambda functions
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Some of Python’s built-in functions (such as zip, sorted, min, max, and round)
Intermediate Python
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Higher order functions (passing and returning functions from functions)
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Maps (dictionaries)
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Closures
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Advanced sorting and filtering
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Decorators – what they are, and how to write your own
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Reading and writing text files
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Python’s module and import system
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How to work with dates and times
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How to read and write CSV files
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Random numbers and sampling
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A look at Python Math and Stats modules
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Decimal data type – for when floats aren’t precise enough
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How to write your own custom Classes (OOP)
3rd Party Libraries
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the pytz library for dealing with timezones and daylight savings
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the dateutil library for parsing date/time strings
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What is JSON data, and how to read and write JSON
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What are REST APIs
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How to use the requests library for HTTP/s requests (and how to interact with a REST API)
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Fundamentals of the NumPy library for fast numerical computations
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Fundamentals of the Pandas library for working with data sets (including indexing)
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Fundamentals of the matplotlib library for charting data
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Lecture 2: (Optional – Skip if you know this) Windows Command Prompt: Primer
Chapter 2: Running Python
Lecture 1: Introduction
Lecture 2: What is Python?
Lecture 3: Installing Python
Lecture 4: Installation – Mac & Linux
Lecture 5: Installation – Windows
Lecture 6: Using the Windows Python Launcher
Lecture 7: Course Materials (Jupyter Notebooks)
Lecture 8: Course Materials (Slides)
Lecture 9: Virtual Environments
Lecture 10: Creating Virtual Environments – Mac & Linux
Lecture 11: Creating Virtual Environments – Windows
Lecture 12: Installing Packages – Lecture
Lecture 13: Installing Packages – Coding
Lecture 14: Running Python – Lecture
Lecture 15: Running Python – Coding
Chapter 3: Python Basics
Lecture 1: Introduction – Python Basics
Lecture 2: Basic Data Types – Lecture
Lecture 3: Basic Data Types – Coding
Lecture 4: Objects – Lecture
Lecture 5: Objects – Coding
Lecture 6: Variables – Lecture
Lecture 7: Variables – Coding
Lecture 8: Arithmetic Operators – Lecture
Lecture 9: Arithmetic Operators – Coding
Lecture 10: Operator Precedence – Lecture
Lecture 11: Operator Precedence – Coding
Lecture 12: Integer Division and Modulus – Lecture
Lecture 13: Integer Division and Modulus – Coding
Lecture 14: Comparison Operators – Lecture
Lecture 15: Comparison Operators – Coding
Lecture 16: Boolean Operators – Lecture
Lecture 17: Boolean Operators – Coding
Lecture 18: Exercises
Chapter 4: Conditional Execution
Lecture 1: Introduction – Conditional Execution
Lecture 2: if…else… – Lecture
Lecture 3: if…else… – Coding
Lecture 4: elif – Lecture
Lecture 5: elif – Coding
Lecture 6: Ternary Conditional Operator – Lecture
Lecture 7: Ternary Conditional Operator – Coding
Lecture 8: Exercises
Chapter 5: Sequence Types
Lecture 1: Introduction – Sequence Types
Lecture 2: Lists – Lecture
Lecture 3: Lists – Coding
Lecture 4: Tuples – Lecture
Lecture 5: Tuples – Coding
Lecture 6: Strings – Lecture
Lecture 7: Strings – Coding
Lecture 8: Slicing – Lecture
Lecture 9: Slicing – Coding
Lecture 10: Manipulating Sequences – Lecture
Lecture 11: Manipulating Sequences – Coding
Lecture 12: Copying Sequences – Lecture
Lecture 13: Copying Sequences – Coding
Lecture 14: Unpacking Sequences – Lecture
Lecture 15: Unpacking Sequences – Coding
Lecture 16: Exercises
Chapter 6: Strings
Lecture 1: Introduction – Strings
Lecture 2: Unicode – Lecture
Lecture 3: Unicode – Coding
Lecture 4: Common String Methods – Lecture
Lecture 5: Common String Methods – Coding
Lecture 6: String Interpolation – Lecture
Lecture 7: String Interpolation – Coding
Lecture 8: Exercises
Chapter 7: Iteration
Lecture 1: Introduction – Iteration
Lecture 2: The range Function – Lecture
Lecture 3: The range Function – Coding
Lecture 4: For Loops – Lecture
Lecture 5: For loops – Coding
Lecture 6: While Loops – Lecture
Lecture 7: While Loops – Coding
Lecture 8: Continue, Break and Else – Lecture
Lecture 9: Continue, Break and Else – Coding
Lecture 10: Exercises
Chapter 8: Dictionaries
Lecture 1: Introduction – Dictionaries
Lecture 2: Associative Arrays and Dictionaries – Lecture
Lecture 3: Associative Arrays and Dictionaries – Coding
Lecture 4: Iterating Dictionaries – Lecture
Lecture 5: Iterating Dictionaries – Coding
Lecture 6: Working with Dictionaries – Lecture
Lecture 7: Working with Dictionaries – Coding
Lecture 8: Exercises
Chapter 9: Sets
Lecture 1: Introduction – Sets
Lecture 2: Python Sets – Lecture
Lecture 3: Python Sets – Coding
Lecture 4: Common Set Operations – Lecture
Lecture 5: Common Set Operations – Coding
Lecture 6: Exercises
Instructors
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Dr. Fred Baptiste
Software Engineer and Mathematician
Rating Distribution
- 1 stars: 11 votes
- 2 stars: 22 votes
- 3 stars: 93 votes
- 4 stars: 511 votes
- 5 stars: 1658 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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