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Introduction to Python Programming

Learn to read, write, and solve real-life problems with Python. (Retiring September 30, 2023)

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About this course

Note: This course is no longer available for registration. You may register for the revised and enhanced Introduction to Python Programming Learning Path, which includes the existing 10 modules as short courses and improved practice quiz questions.

This beginner course is designed to help you learn the foundations of Python quickly so that you can start using Python in the real world as soon as possible! You’ll learn how to read and write code, how to choose and use data structures, and how to recognize and resolve errors. More importantly, we’ll help you understand what to learn “now,” “next,” and “later” so you can focus on the fundamentals first.

By the end of this online course, you’ll understand:

  • How to read and write Python code
  • How to solve problems with loops and functions
  • How to continuously learn and grow with the language

And you’ll be able to:

  • Choose the right data structure for the right problem
  • Effectively create and use objects and functions
  • Resolve problematic pieces of code

This training is for you because:

  • You want to learn how to code (with one of the most popular languages!)
  • You want to become a Backend Developer or Data Scientist
  • You are a developer with experience in another language

Prerequisites: None

To follow along using your desktop IDE:

  1. Install the latest version of Anaconda
  2. Launch your command line tool and configure your conda environment.

For macOS and Linux users: Search and launch Terminal in your system

For Windows users: Locate and launch Anaconda Prompt in your system

3. (Optional but recommended) From the command line, run the following prompts to create and activate a new environment

conda create --name NEW_ENV_NAME

conda activate NEW_ENV_NAME 

4. Add conda-forge as a channel to your environment

conda config --add channels conda-forge 

5. Install required packages in the command line

conda install jupyterlab rich faker chime schedule pandas 

6. Launch JupyterLab from the command line

jupyter lab 

To follow along using Anaconda Notebooks: 

  1. Launch Anaconda Notebooks in a new window.

You may access the instructor's completed notebooks from the Anaconda Notebooks file directory saved under sample_notebooks -> AnacondaLearning -> intro_to_python_programming. 

2. Create a new notebook and install packages. If you are using Anaconda Notebooks to complete this course, you will need to install ipykernel, rich, chime, and schedule from the conda-forge channel.

(Continued) To install and use new packages from conda-forge in Anaconda Notebooks:

  1. Launch the terminal 

Open the terminal from the Anaconda Notebooks launcher. 

2. Create and activate a new environment

conda create -n NEW_ENV_NAME python=3.9

conda activate NEW_ENV_NAME

3. Add channel to your environment

conda config –add channels conda-forge

4. Install packages to your environment

conda install ipykernel chime rich schedule

5. Activate a new kernel from your notebook

Open a notebook file and locate the Kernel menu option. Select Change Kernel from the drop-down menu. Select the kernel with the name of the environment you just created. It should look like ‘.conda-NEW_ENV_NAME.’ Once you’ve selected the kernel, you may use the packages you’ve just installed.

Additional Resources:

Python's math function documentation

Python's Module index

Python's random function documentation

Facilitator Bio:

Max Humber helps individuals, startups, Fortune 500 companies, and (sometimes) government agencies solve problems with technology. He also independently publishes apps at bracket and teaches at General Assembly. Find him at GitHub and LinkedIn.

 

Questions? Issues? Join our Community page to get help. 

Curriculum05:17:20

  • How to Use Anaconda Notebooks
  • Strings
  • Preview
    Strings: String Basics, print, and Variables 00:05:07
  • Strings: Interpolation and string methods 00:07:10
  • Strings Quiz: String Modules
  • Strings: in operator + Challenge 00:05:15
  • Numbers
  • Numbers: Ints, floats, operators, exponents, and brackets + Challenge 00:06:39
  • Numbers Quiz: Math Memes
  • Numbers: Floor division, rounding, modulo operator, and big numbers 00:07:09
  • Numbers: Casting (to and from) + Challenge 00:07:49
  • Bools
  • Bools: assignment, equal to, not equal to, and floating point errors 00:05:55
  • Bools: Greater/less than, between, True/False, not, and Autocasting + Challenge 00:09:48
  • Bools: and, or + Challenge 00:08:53
  • Bools Quiz: True, False, and, or
  • Collections
  • Collections: Lists, indexing, and slicing + Challenge 00:09:18
  • Collections Quiz: Querying a list using an index
  • Collections: Referencing, methods, and extend 00:09:35
  • Collections: More methods and dictionaries 00:05:55
  • Collections: Dictionary methods and sets 00:06:36
  • Collections: Tuples + Challenge 00:07:50
  • Imports
  • Imports: import, from, as, and help + Challenge 00:07:23
  • Imports Quiz: Explore math documentation
  • Imports: Examples from math documentation 00:03:07
  • Imports: Time and itertools 00:07:07
  • Imports: Random + Challenge 00:07:35
  • Imports: Counter (from Collections) + Challenge 00:03:57
  • Imports: Third-Party Libraries + Challenges 00:07:40
  • Functions
  • Functions: Using and creating functions and return 00:07:04
  • Functions: Anatomy of a function and arguments 00:08:59
  • Functions: Default arguments and docstrings + Challenge 00:06:30
  • Functions: Lambda functions and filter 00:07:32
  • Functions Quiz: Fill in the blanks of these functions
  • Functions: Map and reduce 00:05:53
  • Functions: *args, **kwargs + Challenge 00:05:36
  • Rules
  • Rules: if 00:07:15
  • Rules: else and else if (elif) 00:04:21
  • Rules Quiz: Using if, elif, and else statements
  • Rules: Encapsulate + Challenges 00:09:59
  • Repeats
  • Repeats: From map to loop, iterables, and for loops 00:08:26
  • Repeats: FizzBuzz example and enumerate + Challenge 00:09:13
  • Repeats: while loops and infinite loops/break 00:07:38
  • Repeats: List comprehension 00:07:35
  • Repeats Quiz: Understanding iterables
  • Repeats: Recursion and tqdm + Challenge 00:10:21
  • Errors
  • Errors: Common errors, try, try/except/pass 00:09:55
  • Errors: Raise and warnings 00:03:55
  • Errors: Converting warnings and catch_warnings + Challenge 00:06:39
  • Errors Quiz: Understanding errors and warnings
  • Classes
  • Classes: Class examples and __init__ 00:09:29
  • Classes: Class Methods and Properties 00:06:49
  • Classes Quiz: What is a class?
  • Classes: Dunder methods 00:07:00
  • Classes: Operator overloading + Challenge 00:07:51
  • Classes: Inheritance 00:04:14
  • Classes: List encoder + Challenge 00:07:33
  • Conclusion 00:07:45
  • End of Course Survey

About this course

Note: This course is no longer available for registration. You may register for the revised and enhanced Introduction to Python Programming Learning Path, which includes the existing 10 modules as short courses and improved practice quiz questions.

This beginner course is designed to help you learn the foundations of Python quickly so that you can start using Python in the real world as soon as possible! You’ll learn how to read and write code, how to choose and use data structures, and how to recognize and resolve errors. More importantly, we’ll help you understand what to learn “now,” “next,” and “later” so you can focus on the fundamentals first.

By the end of this online course, you’ll understand:

  • How to read and write Python code
  • How to solve problems with loops and functions
  • How to continuously learn and grow with the language

And you’ll be able to:

  • Choose the right data structure for the right problem
  • Effectively create and use objects and functions
  • Resolve problematic pieces of code

This training is for you because:

  • You want to learn how to code (with one of the most popular languages!)
  • You want to become a Backend Developer or Data Scientist
  • You are a developer with experience in another language

Prerequisites: None

To follow along using your desktop IDE:

  1. Install the latest version of Anaconda
  2. Launch your command line tool and configure your conda environment.

For macOS and Linux users: Search and launch Terminal in your system

For Windows users: Locate and launch Anaconda Prompt in your system

3. (Optional but recommended) From the command line, run the following prompts to create and activate a new environment

conda create --name NEW_ENV_NAME

conda activate NEW_ENV_NAME 

4. Add conda-forge as a channel to your environment

conda config --add channels conda-forge 

5. Install required packages in the command line

conda install jupyterlab rich faker chime schedule pandas 

6. Launch JupyterLab from the command line

jupyter lab 

To follow along using Anaconda Notebooks: 

  1. Launch Anaconda Notebooks in a new window.

You may access the instructor's completed notebooks from the Anaconda Notebooks file directory saved under sample_notebooks -> AnacondaLearning -> intro_to_python_programming. 

2. Create a new notebook and install packages. If you are using Anaconda Notebooks to complete this course, you will need to install ipykernel, rich, chime, and schedule from the conda-forge channel.

(Continued) To install and use new packages from conda-forge in Anaconda Notebooks:

  1. Launch the terminal 

Open the terminal from the Anaconda Notebooks launcher. 

2. Create and activate a new environment

conda create -n NEW_ENV_NAME python=3.9

conda activate NEW_ENV_NAME

3. Add channel to your environment

conda config –add channels conda-forge

4. Install packages to your environment

conda install ipykernel chime rich schedule

5. Activate a new kernel from your notebook

Open a notebook file and locate the Kernel menu option. Select Change Kernel from the drop-down menu. Select the kernel with the name of the environment you just created. It should look like ‘.conda-NEW_ENV_NAME.’ Once you’ve selected the kernel, you may use the packages you’ve just installed.

Additional Resources:

Python's math function documentation

Python's Module index

Python's random function documentation

Facilitator Bio:

Max Humber helps individuals, startups, Fortune 500 companies, and (sometimes) government agencies solve problems with technology. He also independently publishes apps at bracket and teaches at General Assembly. Find him at GitHub and LinkedIn.

 

Questions? Issues? Join our Community page to get help. 

Curriculum05:17:20

  • How to Use Anaconda Notebooks
  • Strings
  • Preview
    Strings: String Basics, print, and Variables 00:05:07
  • Strings: Interpolation and string methods 00:07:10
  • Strings Quiz: String Modules
  • Strings: in operator + Challenge 00:05:15
  • Numbers
  • Numbers: Ints, floats, operators, exponents, and brackets + Challenge 00:06:39
  • Numbers Quiz: Math Memes
  • Numbers: Floor division, rounding, modulo operator, and big numbers 00:07:09
  • Numbers: Casting (to and from) + Challenge 00:07:49
  • Bools
  • Bools: assignment, equal to, not equal to, and floating point errors 00:05:55
  • Bools: Greater/less than, between, True/False, not, and Autocasting + Challenge 00:09:48
  • Bools: and, or + Challenge 00:08:53
  • Bools Quiz: True, False, and, or
  • Collections
  • Collections: Lists, indexing, and slicing + Challenge 00:09:18
  • Collections Quiz: Querying a list using an index
  • Collections: Referencing, methods, and extend 00:09:35
  • Collections: More methods and dictionaries 00:05:55
  • Collections: Dictionary methods and sets 00:06:36
  • Collections: Tuples + Challenge 00:07:50
  • Imports
  • Imports: import, from, as, and help + Challenge 00:07:23
  • Imports Quiz: Explore math documentation
  • Imports: Examples from math documentation 00:03:07
  • Imports: Time and itertools 00:07:07
  • Imports: Random + Challenge 00:07:35
  • Imports: Counter (from Collections) + Challenge 00:03:57
  • Imports: Third-Party Libraries + Challenges 00:07:40
  • Functions
  • Functions: Using and creating functions and return 00:07:04
  • Functions: Anatomy of a function and arguments 00:08:59
  • Functions: Default arguments and docstrings + Challenge 00:06:30
  • Functions: Lambda functions and filter 00:07:32
  • Functions Quiz: Fill in the blanks of these functions
  • Functions: Map and reduce 00:05:53
  • Functions: *args, **kwargs + Challenge 00:05:36
  • Rules
  • Rules: if 00:07:15
  • Rules: else and else if (elif) 00:04:21
  • Rules Quiz: Using if, elif, and else statements
  • Rules: Encapsulate + Challenges 00:09:59
  • Repeats
  • Repeats: From map to loop, iterables, and for loops 00:08:26
  • Repeats: FizzBuzz example and enumerate + Challenge 00:09:13
  • Repeats: while loops and infinite loops/break 00:07:38
  • Repeats: List comprehension 00:07:35
  • Repeats Quiz: Understanding iterables
  • Repeats: Recursion and tqdm + Challenge 00:10:21
  • Errors
  • Errors: Common errors, try, try/except/pass 00:09:55
  • Errors: Raise and warnings 00:03:55
  • Errors: Converting warnings and catch_warnings + Challenge 00:06:39
  • Errors Quiz: Understanding errors and warnings
  • Classes
  • Classes: Class examples and __init__ 00:09:29
  • Classes: Class Methods and Properties 00:06:49
  • Classes Quiz: What is a class?
  • Classes: Dunder methods 00:07:00
  • Classes: Operator overloading + Challenge 00:07:51
  • Classes: Inheritance 00:04:14
  • Classes: List encoder + Challenge 00:07:33
  • Conclusion 00:07:45
  • End of Course Survey