Python for Kids: a 30-Day Roadmap

Published October 13, 2023

Python is the top programming language by popularity. It is also a relatively easy language to learn, with an easy syntax. It is useful in various areas, including artificial intelligence. Python is taught in various stages in schools, usually in high school and different school clubs.

Python learning for children, elementary, middle and high school

Elementary school kids can also learn Python with a little effort. This blog post gives a timeline or roadmap on the sequence for children to learn Python. The recommended ages are 10 and above. There are always outliers -- for example, in my experience, a 9-year old elementary school student may learn Python faster than a college student who may find Python intimidating or difficult to learn.

This blog post is not a tutorial on how to set up Python on your computer or how to code in Python. This is only a roadmap for learning core Python basics in 30 days.

Day 1

Install Python 3.11 or 3.10, the most recent version is preferable. Preferred editors and IDEs are Visual Studio Code with Python plugin and Sublime Text.

Write a simple Hello World program and make sure it executes.

Day 2

Learn the basics about Python variables, operators and basic data types -- int, float, str, bool, None, list. Practice with a little of each. You will be working on these in-depth later.

Day 3

Learn more data types -- complex, tuple, set, frozenset, range, dictionary, bytes, bytearray. Practice with a couple examples for each data type.

Day 4

More operators -- Arithmetic, Assignment, Comparison, Logical, Identity, Bitwise and Membership operators. Practice.

Day 5

Learn about blocks, and conditional statements if along with pass, break, continue. Learn about nested if statements. Practice.

Also, practice using the bool data type.

Day 6

Learn about for loops. Practice.

Day 7

Learn about while loops. Practice.

Day 8

Learn more about strings. Learn and practice using various string operations.

Also, learn string formatting using the format() method and f-strings.

Day 9

Learn more about lists and list operations. Learn about tuples as well. Practice.

Learn about iterators and how to use __iter__() and __next__() methods.

Day 10

Learn more about dictionaries. Learn and practice using various dictionary operations. Pay special attention to methods such as .keys() and .values().

Day 11

Learn more about sets and frozen sets. Practice.

Day 12

Learn how to create lists from dictionaries and using the zip function.

Day 13

At this point, if you are comfortable about lists and dictionaries, practice with exercises that use lists of lists, lists of dictionaries and dictionaries of lists.

Day 14

Learn how to convert string to bytes, and bytes to string.

In particular, the decode() method and str() function.

Day 15

Learn about functions and modules in Python. Learn how to call existing functions and create new functions. Learn about arguments and how to pass them.

Learn about arbitrary arguments args and keyword arguments *kwargs.

Learn about named arguments.

Learn about the main() function in Python.

Day 16

Learn about local scope and global scope.

Learn about recursion and practice it.

Learn about lambda in Python. Practice.

Day 17

Learn about map(), filter() and reduce. Learn about list comprehension too. You will be using more of list comprehension.

Day 18

Learn about exception handling in Python.

Day 19

Learn about creating and reading JSON objects in Python. Convert between JSON and dictionaries.

Day 20

Learn about file handling in Python. Learn and practice reading a file, writing to a file, appending to a file.

Day 21

Practice more file handling and file operations exercises.

Day 22

Learn about regular expressions in Python. Spend as much time as you can with this.

Day 20

Practice more regular expressions.

Day 21

Learn the concept of object-oriented programming in Python. Practice the PIE concepts -- polymorphism, encapsulation and inheritance.

Day 22

Practice more object-oriented examples with Python.

Learn about Python's new dataclass.

Day 23

Learn about pip and install the requests package with:

pip install requests

Learn about requests package and practice using it to make remote HTTP calls. Practice retrieving the IP address from https://api.aruljohn.com/ip in plaintext format and from https://api.aruljohn.com/ip/json in JSON format.

Day 24

Practice more with requests and learn how to use sessions. If you are feeling adventurous, install and try selenium.

Day 25

Learn how to use the built-in functions such as help(), type(), and other methods.

Learn how to use dates in Python using the datetime module.

Day 26

Learn the various math functions. Also, install the math module and practice as many math functions as you can.

Day 27-28

Work on a small project that should take you a couple of days .

Make sure it has an input file to read from, regular expressions, making remote HTTP calls, parsing the response as JSON, formatting the response and printing the result. Get creative with your self-defined question if you cannot find one. Or contact me and I can give you project ideas.

Day 29

Learn about multithreading. Practice an example using multithreading.

Day 30

Learn about making asynchronous http requests using aiohttp. Practice an example using aiohttp.

Everyone's timeline is different

Everyone's timeline is different. For some, this 30-day timeline may be too basic. For others, this may be complex.

The trick is to adapt this timeline to suit your own pace and convenience. You may find a few topics easy and other topics harder to master. It is totally fine. Just learn the topics gravitate and learn naturally. Good luck on your Python journey!

What next?

What you have learned after these 30 days of Python is a little more than core Python. After this, you can improve on it by practicing Python on HackerRank, LeetCode and other online competition websites.

If you want to progress to a specific field, you can move on to learning new modules and packages to work with data science, web development, automation, scraping, data analytics, machine learning, artificial intelligence and a lot more. On this website, you will find code samples. In addition, I will be posting more code samples regularly. If you have any requests for code samples, please email me.

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If you have any questions, please contact me at arulbOsutkNiqlzziyties@gNqmaizl.bkcom. You can also post questions in our Facebook group. Thank you.

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Last Updated: October 13, 2023. ย ย ย  This post was originally written on August 21, 2023.