Python The 2024 Road Map To Master It All

Python Road-map

Python can do anything. All including Data Science, Machine Learning, Deep Learning, NLP, Image/Video Processing for both Detection and Segmentation, Games, Android, Web Apps , Desktop GUI , You Just name it.

The thing is, if you want to learn it all, this can be a bit overwhelming. By the end of this article, you will see how you can master all of those topics.

The Python 2023 Roadmap:

This mind map summarizes all the libraries (and basic python concepts) that you can learn to master it all. This is not a very long run. You should be able to master all of those topic in a shorter amount of time than you think, because python takes care of most of the code for you, due to its HUGE library support.

1. Let’s start with Python Basics:

1. Learn all about Variables and String Manipulation. This is essential for any topic that comes later.
2. Conditional statements and how to make program decisions
3. Loops, and focus on for loops advanced syntaxes like zip and enumerate. Those are utterly useful if you want to code in the “Pythonic” way.
4. You MUST master data structures like Lists and Dictionaries, less important structures would be Tuples and Sets
5. Learn all about Functions and how to Return values from them. Make sure you understand data scopes and Global variables
6. Learn Advanced Built-in functions like List Comprehension, Maps and Lambda Functions
7. Exceptions are essential to write a code that is , as much as possible crash Free
8. Directory Management which is used to create directory trees for your project files. And it is very useful for Tasks Automation, File Navigation ..etc. Read about it.

2. Python Object Oriented Programming (OOP):

In the world of modern software, one cannot ignore the importance of maintainable easy to extend code.

So here is what you need to know:

1. Classes and how to create class methods, class variables and Class initializer
2. Object, which is nothing but a class in play
3. Inheritance
4. Super keyword
5. Polymorphism
6. Encapsulation
7. If you really want to go the extra mile, check out Design Patterns
8. This one is not really related to OOP, but Decorators which are Python specific techniques can be very helpful when working with a lot with external libraries like Unittest. Which is very popular for testing your software.

3. Python File Handling:

The following files formats are essential to work with. And Python is the best programming language to edit, script and automate whatever realted to those file formats.

1. .txt
2. .csv
3. .pdf
4. .json
5. .zip

4.Python Math Library:

It is necessary that math computation should be fast, and python, kind has the reputation of being slow compared to C/C++.

Well, this is not entirely true. In Python we use a library called Numpy to perform almost any Complex math operation. Be it matrix multiplication, be it searching an array for an element or finding Max/Min elements.

The library is huge, but here is some highlights on what you need to learn to get started:

1. Single Arrays
2. Multi-dim Arrays
3. numpy Search Functions
4. numpy max/min functions
5. numpy sorting functions
6. converting string_to_array and vica versa
7. Split
8. Randomized arrays
9. Reshaping arrays
10. Inverting an array
11. Array multiplication techniques

5. Python Tabular Data Manipulation with Pandas:

Pandas is the to-go library when handling any Tabular data (like excel files, csv..etc).

Imagine being able to automate anything that excel can do, and add it to the vast enormous Python world.. well that is exactly what is this library all about. Here is some highlights on where you need to start:

1. Pandas Dataframes
2. Reading csv files
3. Data filters
4. Column manipulation
5. Rows manipulation
6. Renaming elements
7. Series
8. Internal Plotting Functions
9. Generating CSV files

6. Python Image and Video Processing:

It is a wild statement to say that Python can replicate all of those Photo/Video Apps you see around. Because Python combined with OpenCV is a giant monster when it comes to media file manipulation.

Here is some highlights on what’s necessary to start with:

1. Understand Color Spaces (RGB, HSV, LAB)
2. Reading/Writing Images
3. Display Images
4. Binarizing images
5. Thresholding Techniques
6. Image Manipulation (Rotate, Scale…)
7. Array to image conversion and vice versa
8. Dilation and erosion
9. Contour Detection
10. Contour Drawing
11. Shape Approximation
12. Contour Area calculation
13. Masking

Now everything you applied to images, can be applied to video, because a video is nothing but a series of images displayed at a certain rate.

The only thing I can add here is Object Tracking , take a look at it.

7. Python User Interfaces (UI):

How would you get rid of that “code view” and use some Interactive interfaces instead. Isn’t that what all software have in common?

Python has multiple forms of user interface.

1. Command Line Interfaces, which is as the name implies, it is based on a command line window, where you type instructions which your python script would execute.
   You can use Argparse library for that
2. Desktop GUI, or graphical user interfaces. This would make your software look like any other software you download and install with interactive button, text fields, dropdown lists and menus.
   You can use PySimpleGUI or Tkinter.
3. This will create a user interface in your browser. The advantage of that type of UI is that you can simply deploy your project on the web later along with that interface. This advantage cannot be found in Argparse or Tkinter

8. Python Data Visualization:

Having data, be it internal python data or external tabular data requires some visualization right?

The most important two libs are:

1. Matplotlib
2. Seaborn

Matplotlib is more flexible to use, but Seaborn has a more beautiful visualization. In general here is the most important topics to learn about any of them

1. Histograms
2. Scatter Plotting
3. History Formation
4. Pair plots
5. Coloring Data
6. Multiple Plots
7. Live Plots

9. Python Multithreading:

Now that you have learned some Python coding, you will realize that executing’s one instruction at a time is not practical in most large applications. Like sometimes you would like to have your GUI running independently of the python other functions.

And here comes multithreading.

1. Starting a thread
2. Join
3. Thread pool
4. Semaphores

The topic is pretty large, but those should be enough to get you started.

10. Python Task Automation

Automating the “Boring Tasks’ , like Excel File , webforms and GUI logging can be easily automated with python. You can even create python scripts just to play your favorite Android/OS game and collect all the daily rewards for you!

The following libraries are the most famous for this:

1. Selenium
2. pyautogui
3. OpenCV can prove very useful when integrated with the above mentioned

Here is a highlight of what you need to start with:

1. XPATH web-page Extraction to interact using selenium
2. filling text fields
3. clicking
4. finding an element either by xpath or using a template image
5. handling dropdown menus
6. Handling file uploads
7. learning template matching in OpenCV

Python All In-One

11. Python Data Science and Machine Learning:

Supervised learning, unsupervised learning, Reinforcement learning , all of those exciting topics can be learned through programming them with python. Since programming with hands on application will increase your learning rate x10 folds, consider learning the algorithm and playing around with in python immediately.

The two most famous library for data science and machine learning are:

1. scipy
2. sklearn which is built upon scipy

Initially you can stick to sklearn. Here are the top algorithms that you can start with:

1. Supervised learning:
   a. Naive Bayes
   b. Linear Regression
   c. SVM
2. Unsupervised Learning:
   a. K-means clustering
   b. PCA
   c. LDA
   d. t-SNE
3. Reinforcement Learning:
   a. Q-learning
   b. Genetic Learning

It’s important also to familiarize your self with Machine Learning models evaluation techniques :

1. Accuracy
2. Confusion Matrix
3. AUC/ROC Curves
4. Cross fold

12. Python Deep Learning:

This topic is built on Python Machine Learning, and it utilizes essentially Neural Networks. This is a whole domain of specialization now.

You need to check out Tensor Flow, Keras and Pytorch.
Start with Keras (built on Tensor flow) then you can jump to Pytorch.
Since Keras functions are easier to handle than Pytorch.

Here are the first algorithms that you need to start with

1. Deep Artificial Neural Networks (ANN). Perfect for regression prediction tasks
2. Convolutional Neural Networks (CNN) this is perfect for image classification
3. Generative Adversarial Networks (GAN). The basis of Deep Fake and fake data generation

Make sure you learn all the common technicalities that comes with all deep learning models like:

1. Loss Functions and Backpropagation
2. Activation Functions
3. Training/Testing Accuracy/Loss
4. Fine Tuning

Those should be enough to get you started

13. Python Web Design:

Yes, you can actually design backend for your web pages with Python. Actually libraries like Flask can be the most user friendly one to get you started. To be honest, it would be super helpful to have some knowledge in at least HTML/CSS to be able to test out what’s going on through your Font-End (Front end being all of flashy buttons and menus you see on a page).

However, if you are fine with writing super dummy pages using Flask internal functions, then be my guest and get started!

Here is what you need to start with:

1. Routes
2. Navigation
3. Templates
4. Updating Page elements through Python
5. Session
6. Authentication

Would you like to learn all of this, and even more?

You definitely should check This Course out.
This is the only course on the internet that gets weekly updates with a new section.
Since the goal here, is that this course includes everything that you would ever need in python. You don’t need to buy 20 courses to master python.

You can ask the instructor to add any topic regarding Python and he will add it within a week!! No additional costs!

Python All In-One 2023 ™️ -Everything You’ll Ever Need