Python opens the door for multiple career options.
These 9 key topics will be essential in your Python journey.
These 9 key topics will be essential in your Python journey.
Before we begin, I'll introduce you @brilliantorg
I am amazed to find
⬘ courses over there are super interactive
⬗ topics are explained from very basics
⬙ plenty of exercises
⬖ everything over there is fun to learn
Don't go by my words. Check how it explains:
I am amazed to find
⬘ courses over there are super interactive
⬗ topics are explained from very basics
⬙ plenty of exercises
⬖ everything over there is fun to learn
Don't go by my words. Check how it explains:
First thing: Why Python?
⬘ One of the simplest programming language and very easy to start.
⬗ Easy to extend any feature using the rich set of packages it provides.
⬙ Most popular and heavily used in Data Science, AI/ML, and Web Dev.
The next question: How should we start?
⬘ One of the simplest programming language and very easy to start.
⬗ Easy to extend any feature using the rich set of packages it provides.
⬙ Most popular and heavily used in Data Science, AI/ML, and Web Dev.
The next question: How should we start?
➊ Working with Data [1]
Learn about basic data and corresponding data types.
➀ Boolean Type
❯ bool
➁ Number Type
❯ int
❯ float
❯ complex
➂ String Type
❯ str
➃ Bytes Type
❯ bytes
❯ bytearray
❯ memoryview
Learn about basic data and corresponding data types.
➀ Boolean Type
❯ bool
➁ Number Type
❯ int
❯ float
❯ complex
➂ String Type
❯ str
➃ Bytes Type
❯ bytes
❯ bytearray
❯ memoryview
➋ Working on Logic
Logic is very important while solving any problem. 3 important features are:
➀ Operators
❯ Arithmetic
❯ Assignment
❯ Comparison
❯ Logical
➁ Conditionals
❯ If
❯ Else
❯ Elif
➂ Loops
❯ while
❯ for
Logic is very important while solving any problem. 3 important features are:
➀ Operators
❯ Arithmetic
❯ Assignment
❯ Comparison
❯ Logical
➁ Conditionals
❯ If
❯ Else
❯ Elif
➂ Loops
❯ while
❯ for
➌ Modularize your Code
A large piece of code is difficult to test and maintain. Divide your code into smaller and meaningful units.
➀ Function
❯ Definition
❯ Arguments
❯ Return
❯ Execution
➁ Module
❯ Define
❯ Import
➂ Scope and Namespace
A large piece of code is difficult to test and maintain. Divide your code into smaller and meaningful units.
➀ Function
❯ Definition
❯ Arguments
❯ Return
❯ Execution
➁ Module
❯ Define
❯ Import
➂ Scope and Namespace
➍ Working with Data [2]
Like atoms combine to form molecules, simple data types also combine to form many complex types.
They represent specific data structures and can execute operations on data efficiently.
➀ list
➁ tuple
➂ set
➃ frozenset
➄ dict
Like atoms combine to form molecules, simple data types also combine to form many complex types.
They represent specific data structures and can execute operations on data efficiently.
➀ list
➁ tuple
➂ set
➃ frozenset
➄ dict
➎ Working with Data [3]
Python has a lot of modules that are meant for efficient usage and operation of different types of data.
Some important modules are:
❯ datetime
❯ csv
❯ json
❯ logging
❯ os
In addition, learn about:
❯ Files
❯ String Formatting
❯ Named Tuple
Python has a lot of modules that are meant for efficient usage and operation of different types of data.
Some important modules are:
❯ datetime
❯ csv
❯ json
❯ logging
❯ os
In addition, learn about:
❯ Files
❯ String Formatting
❯ Named Tuple
➏ A little advanced
Python provides a lot of syntactic sugars for writing codes efficiently.
Below are some of those important features that we should make our hands dirty with:
❯ Iterators
❯ Generators
❯ Closure
❯ Decorators
❯ Exception Handling
Python provides a lot of syntactic sugars for writing codes efficiently.
Below are some of those important features that we should make our hands dirty with:
❯ Iterators
❯ Generators
❯ Closure
❯ Decorators
❯ Exception Handling
➐ Object Oriented Programming
So far we have followed procedural programming. OOP can help us organizing our code for maximum reusability.
❯ Class
❯ Variable
❯ Method
❯ Static Method
❯ Magic Method
❯ Overloading
❯ Inheritance
❯ Property Decorators
So far we have followed procedural programming. OOP can help us organizing our code for maximum reusability.
❯ Class
❯ Variable
❯ Method
❯ Static Method
❯ Magic Method
❯ Overloading
❯ Inheritance
❯ Property Decorators
➑ Take it to next level [1]
Great thing about Python is that it has a rich set of packages. But how can we easily manage and use those in our projects?
If you are for Data Science or AI/ML (like me), these tools helps a lot:
❯ Jupyter Notebook
❯ Spyder
❯ pip
❯ anaconda
Great thing about Python is that it has a rich set of packages. But how can we easily manage and use those in our projects?
If you are for Data Science or AI/ML (like me), these tools helps a lot:
❯ Jupyter Notebook
❯ Spyder
❯ pip
❯ anaconda
➒ Take it to next level [2]
Below packages are very useful in computing, scientific analysis, and visualization.
We'll be using them very frequently:
❯ numpy
❯ pandas
❯ matplotlib
❯ scipy
Below packages are very useful in computing, scientific analysis, and visualization.
We'll be using them very frequently:
❯ numpy
❯ pandas
❯ matplotlib
❯ scipy
We just laid out a roadmap. Next thing is, where to learn them?
Brilliant offers 3 courses where you can learn about
➀ Thinking in Code
➁ Programming with Python
➂ Next steps in Python
If you want to start now, hit the links provided in the next tweet.
Brilliant offers 3 courses where you can learn about
➀ Thinking in Code
➁ Programming with Python
➂ Next steps in Python
If you want to start now, hit the links provided in the next tweet.
Python is a key skill and opens the door for various career options.
The best you can do now is start learning from @brilliantorg for free.
If you like it, you can get a 30-day free trial + 20% off for the first year by using this link: brilliant.org
Learn with fun!
The best you can do now is start learning from @brilliantorg for free.
If you like it, you can get a 30-day free trial + 20% off for the first year by using this link: brilliant.org
Learn with fun!
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