Python Developer Roadmap: How to become a Python Developer?

Python Developer Roadmap: How to become a Python Developer?

13 Feb 2024
Beginner
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Python Developer Roadmap: An Overview

Python is one of the most popular programming languages. It is very beneficial for an enthusiastic technocrat in today's world to learn Python and get access to a wide range of opportunities. In this Python tutorial, we will look into the details of the step-by-step procedure on how to become a Python developer.

Who is a Python Developer & What Do They Do?

A software engineer or programmer with expertise in creating, managing, and refining applications utilizing the Python programming language is known as a Python developer. Python is a well-liked general-purpose, high-level programming language that is easy to learn and use. It is extensively utilized in many domains, including automation, scripting, artificial intelligence, machine learning, data science, and web development.

Roadmap to learn Python

This Python developer roadmap covers the core abilities that any Python developer should be familiar with, such as Python syntax and data structures, essential Python frameworks, the importance of data science, and machine learning skills, which are in high demand in almost all industries today. Let's delve into it.

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1. Learning the Basics of Python

First of all, go to Python's official website and download the latest version. Once the installation is done, you can write and run Python code with IDE.

Start with the foundational topics to get a grip on your fundamentals. The following topics will be covered under this:

2. Python Object Oriented Programming (OOP)

The following topics you need to study here:

  • Classes
  • Object
  • Inheritance
  • Data Abstraction
  • Polymorphism
  • Encapsulation

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3. Frameworks & Libraries

Frameworks are collections of core software modules that comprise pre-written code that programmers may utilize to address typical programming tasks. Using frameworks, developers may build project-specific functionality without starting from scratch. Frameworks reduce the amount of code that one has to write. Thus making programming more efficient. Understanding these frameworks and libraries is critical to speed development and creating efficient and scalable applications.

  1. Web Development: Let us learn about the various Python libraries used for web applications.

    1. Django

    It is a high-level Python web framework helpful for quickly and efficiently constructing web applications. It follows the Model-View-Controller (MVC) architectural pattern, making it simple to create sophisticated web applications with a well-defined structure. You must know its built-in admin interface and powerful object-relational mapper for developing scalable, maintainable online applications that are simple to install and manage.

    2. Flask

    It is a micro web framework to build a simple website. It is much easier to learn than Django. Flask provides a wide range of extensions, which can be used to add features such as authentication, database integration, and more. Flask is also known for its flexibility, allowing developers to create applications in various ways.

    3. FastAPI

    It is a high-performance Python web framework for quickly and efficiently constructing APIs. It is intended to be simple to use and quick to develop, making it a popular choice for developers looking to build robust APIs. FastAPI is a significant addition to any Python developer's toolkit due to its current features and emphasis on performance.

  2. Desktop Applications: Now let us look at the various Python libraries used to create desktop applications.

    1. Tkinter

    It is a GUI (Graphical User Interface) toolkit included with Python. Tkinter is an open-source library and it allows you to build desktop GUI applications using Python. To create interactive and user-friendly desktop programs, Python developers must thoroughly understand Tkinter. To develop interactive interfaces, Tkinter provides a variety of widgets such as buttons, labels, menus, and many more.

    2. PyQT

    PyQt is a Python binding of the well-known cross-platform Qt framework, which is used to create graphical user interfaces (GUIs) for desktop and mobile applications. PyQt has several tools and features for developing powerful graphical user interfaces, such as drag and drop, keyboard shortcuts, menus, and dialogues.

  3. Data Visualization: It's time to have a look at various Data Visualization libraries offered by Python.

    1. Matplotlib

    Matplotlib offers a wide range of plotting capabilities and assists developers in creating high-quality data representations. Knowing Matplotlib is essential for Python data analysis and visualization activities. It is widely used to create bar charts, line plots, histograms, and other graphs. Matplotlib is a powerful tool in any Python developer's tool set due to its user-friendly syntax and various features.

    2. Seaborn

    Seaborn is based on Matplotlib and offers a higher-level interface for creating beautiful and useful visualizations with less code. In addition, the library supports various visualization types, such as heatmaps, scatterplots, and line plots, and includes features such as color palettes and statistical analysis tools. As a result, Seaborn is extremely effective for studying and displaying large amounts of data.

  4. Machine Learning

    1. TensorFlow

    It is the most popular deep learning library developed by Google. It is a computational framework that expresses algorithms that involve numerous Tensor operations.

    2. Scikit-Learn

    A machine learning library for Python, designed to work with numerical libraries such as SciPy & NumPy.

    3. PyTorch

    It can handle dynamic computation graphs on the go. It also provides an easy-to-use API.

4. Python Multithreading

The following topics you need to learn here:

  • Starting a thread
  • Join
  • Thread pool
  • Semaphores

5. File Handling in Python

Python is the best programming language to edit, script, and automate whatever is related to the below file formats.

  • .txt
  • .csv
  • .pdf
  • .json
  • .zip

6. Take relevant courses

Some courses you might take are data science fundamentals with Python, Python for cybersecurity, and statistics with Python. You will get good exposure to various problem-solving techniques in such courses.

We, at ScholarHat also offer the following course to help you improve your Python development skills:

7. Build a Nice Portfolio with Projects

As a Python developer, building a strong portfolio with projects is crucial for demonstrating your skills and experience to potential employers or clients. Focus on creating high-quality projects that solve real-world problems and demonstrate your expertise.

8. Take an Internship

Internships are an amazing opportunity to gain real-world experience, learn new skills, and network with industry professionals. Through internships, you get to work on real projects and collaborate with experienced developers, explore different industries and technologies, gain valuable experience, expand your network, and increase your chances of success as a Python developer.

15. Develop a Good Network

Developing a good network is crucial for finding job opportunities and advancing your career. Networking involves building professional relationships with people in your industry, such as colleagues, mentors, recruiters, and alumni. Networking can be done both in-person and online through social media platforms such as LinkedIn.

By attending Python conferences, you can learn different ideas and techniques for coding and observe new programming products. Various experts share their ideas at these conferences. You can have productive discussions with other Python developers and get advice about how to enhance your work.

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Summary

Hence, in the above article, we explored in quite detail the complete roadmap for becoming a Python developer to build their career in the AI-driven world. The only requirement here is dedication and consistency. There may come many a time that you won't be able to understand many concepts. Just remain patient and try to understand calmly. You will surely get through it.

FAQs

Q1. What are the topics to learn in Python Multithreading?

The following topics you need to learn here:
  • Starting a thread
  • Join
  • Thread pool
  • Semaphores

Q2. What are the various Machine Learning libraries in Python?

1. TensorFlow
2. Scikit-Learn
3. PyTorch

Q3. How is Django helpful?

It is a high-level Python web framework helpful for quickly and efficiently constructing web applications. It follows the Model-View-Controller (MVC) architectural pattern, making it simple to create sophisticated web applications with a well-defined structure.

Q4. What are the topics to start with while learning Python?

Start with the foundational topics to get a grip on your fundamentals. The following topics will be covered under this:
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About Author
Sakshi Dhameja (Author and Mentor)

She is passionate about different technologies like JavaScript, React, HTML, CSS, Node.js etc. and likes to share knowledge with the developer community. She holds strong learning skills in keeping herself updated with the changing technologies in her area as well as other technologies like Core Java, Python and Cloud.

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