After Python, What Should I Learn
Python is a programming language used to create websites, software, and other projects. It is easy to code and easy to learn. After learning Python, there are many different directions depending on their interest.
If one is interested in programming, they can prefer learning advanced data structures (ADS); if one is interested in machine learning, they can learn pre-defined libraries in Python and so on.
Different categories are given below, which can be done after Python
Programming using Python
If you are interested in coding and getting advanced in your concepts, Python is an easier way compared to other programming languages.
As Python is easy to code and understand, it is advised to do programming in Python for beginners. Depending on the problem, various data structures such as stacks, queues, linked lists, trees, graphs, and heaps can be used. So, after learning Python, it is better to get advanced in these concepts to get high-paying jobs related to programming.
Machine Learning and Deep Learning using Python
Nowadays, machine learning is an emerging technology. It prepares the computer model according to the user’s requirements.
There are pre-defined libraries in Python, which help in doing machine learning projects.
The libraries are:
- Numpy: Numpy is used to do mathematical operations with the data set. It is used for operating arrays in Python.
- Pandas: Pandas are used in data analysis and data cleaning based on the requirements. It is specially used for machine learning tasks.
- Matplotlib: It is a Python library that visualises the data and creates graphs based on the dataset.
- TensorFlow: Google creates the TensorFlow library. It is used in running neural networks.
- Scikit-learn: Scikit-learn contains all machine learning algorithms, such as supervised and unsupervised. We can import all classifiers using the Scikit-learn library.
- Scipy: It is the scientific library in Python. This is used in image processing. It is one of the important libraries in doing machine learning-related projects.
Web Development
Everyone has their way of designing and visualising. Web development is the creation of art to design websites. This is an interesting course because everyone has their website design ideas. If we learn web development, there are many jobs related to this.
To learn Web Development, there are libraries in Python such as:
- Django: Django is a pre-defined library that is used to maintain websites securely. It is mainly used to provide a strong backend for the website.
- Flutter: It is a development kit to maintain the front-end part of the websites.
- Front-End: It is part of the development where a user can see and interact with the server. This comes under web designing.
- Back-End: It is part of web development which operates at the back of the sites. This mainly comes under server maintenance.
App/Game Development
In modern times, the development of apps and games is increasing rapidly. Because everyone is accustomed to the software devices and these devices are groups of apps. Even a small app with new advantages can greatly impact the present world.
Modules used for app and game development are:
- Pygame
Pygame is a module that is used especially for designing video games. It is portable and can run on any device. By using Pygame, we can design multimedia applications and design art.
- PyCharm
This integrated module creates a balanced and convenient environment for apps.
Web scraping
It is the technique used to obtain a large amount of data from websites. Web scraping a web page involves fetching it and extracting from it. Fetching is the downloading of a page (which a browser does when a user views a page). Therefore, web crawling is the main component of web scraping to fetch pages for later processing.
Pre-defined libraries used for Web scraping are:
Scrapy
It is one module that extracts information from websites based on user requirements. The Scrapy framework provides powerful features such as auto-throttle, rotating proxies and user agents, allowing you to scrape virtually undetected across the net. Scrapy also provides a web-crawling shell, which developers can use to test their assumptions on a site’s behaviour.
Advantages of Web scraping
- Price comparison
- Data extraction
- Searching for information is done by using web scraping.
Data Analyst
You can choose data analyst field, which is done using Python. Data analysis is processing the data and preparing the data from the dataset. Due to rapid data growth, data analysts have huge demand. They are responsible for properly organising the data.
Data analyst Modules:
- Keras: Keras is a deep learning and neural network framework. Keras contains numerous implementations of commonly used neural-network building blocks such as layers, objectives, activation functions, optimisers, and a host of tools to make working with image and text data easier to simplify the coding necessary for writing deep neural network code.
- Py Brain: Py Brain provides an opportunity for advanced research. It is short for Python-Based Reinforcement learning, Artificial Intelligence and Neural Network Library.
Apart from all these, we can develop projects for our users using Python. Using Python, we can create like, Password generator, Alarm, Small games, Weather app, etc.