Why and How To Learn Python

5 reasons to learn Python right now

(1) Easy to learn: Python is the easiest programming language to learn.

(2) High Salary: Did you know that the average Python programmer in the U.S. makes approximately $116 thousand dollars a year.

(3) Scalability: It’s true, Python is easy to learn. But it’s also an extremely powerful language that can help you create top-tier apps. In fact, Google, Instagram, YouTube, and Spotify are all built using Python.

(4) Versatility: What’s more, Python is by far the most versatile programming language in the world today! From web development to data science, machine learning, computer vision, data analysis and visualization, scripting, gaming, and more, Python has the potential to deliver growth to any industry.

(5) Future-proof Career: The high demand and low supply of Python developers make it the ideal programming language to learn today. Whether you’re eyeing a career in machine learning or artificial intelligence, learning Python is an invaluable investment in your career.

You can learn Python on weekends if you know C++ or Java but if you really want to be able to develop application using Python then you will have to plunge into it and I can bet once you do that you will never want to come out of that.When it comes the matter of being worth then…I would say…If you learn Java for 3 months if you are a jobless then it’s not sure whether you might get a job or not but if you know Python and give your 3 months to learn its framework or related stuffs (for which 3 months is enough) then I can guarantee that you wont be jobless ever.

Advantages Of Learning Python :

1. Python is an especially profitable programming language. Like Java, JavaScript, and Ruby, Python abilities can lead to some extremely rich employment pathways.Only in the last three years has Python’s worth increased significantly. In addition to its high average wage, Python is a wise investment because, compared to Ruby, the current top earner, it offers more job market advantages.Any programming language’s viability depends on how well it works and how widely it can be used. Python compares favorably in both of these crucial areas, which is good news for its market value.

2. Python is employed in the cutting-edge fields of machine learning and artificial intelligence.Machine learning and artificial intelligence are used in everything from Uber’s estimated arrival time to Google finishing your sentences and Netflix figuring out which shows you’ll like.It’s exciting to consider where we’re going if we take a moment to recognize how recent many of these advances are. Without a doubt, Python will lead the way in AI innovation.

3. Python is well laid out and simple to learn.Learning Python is an excellent place to start if you’re intimidated by coding or wondering if it’s right for you.Python was created with user-friendliness in mind and had a syntax more similar to English than any other language.

4. Data science is Python’s super great best pal.Python is riding along in what may be the trendiest professional sector of 2020: data science. In case you’re wondering what data science is in the first place, let’s go back a step.In a nutshell, data science is the alchemy of technology: it transforms massive volumes of data into priceless knowledge. Businesses then use that knowledge to create original fixes for issues they might not have otherwise been able to identify.

5. Python programming can be used for various purposes and platforms.

Python is known as the “Swiss Army Knife” of programming languages. Python has practically infinite potential in terms of applications. Constructing a website? Python is capable of doing that. Consider web frameworks. Yep. We know that it works wonders for data mining, but what about creating video games? Yes, even a little game creation.

Read Before You start learning python :

1.Find Out your interest –

Before starting learning about Python, it is very important to understand your areas of interest.

This step will add more fun to your learning and will also keep you motivated. Some areas which you can explore with Python include AI, Machine Learning, App Development, Web Development, etc.

2.Practice Daily – Consistency is power. If you want to master Python, it is very important to practice Python coding regularly. By the time, you will become a master and get familiar with Python.

Interact with the people working in the same field – Python has the largest community. By Contacting experienced people, you can easily discuss your doubts with them or participate in discussions. You can also join online forums to get in touch with Python experts and improve your knowledge with efficiency.

3.Focus on Basics – Basics are the key to learn anything easily. It is very important to learn python syntax before focusing on other aspects.Once you get familiar with basics, then you can focus on Python coding.You can easily address the doubts which may arise in the future with the help of Python Syntax.

5. Start Working on small projects – Working on small projects will help you understand the Python more deeply. Some projects include tic-tac-toe games, an alarm clock app, etc.

Learning Python can be an exciting journey ,Below is a step-by-step guide with a suggested syllabus to help you get started:

Step 1: Understand the Basics

Introduction to Python: Familiarize yourself with Python’s history, features, and use cases.
Installation and Setup: Install Python on your computer and set up the development environment (IDE or text editor).
Writing Your First Python Program: Learn how to write a simple “Hello, World!” program and run it.

Step 2: Python Fundamentals

Variables and Data Types: Understand different data types in Python, such as numbers, strings, lists, tuples, dictionaries, etc.
Operators: Learn about arithmetic, comparison, assignment, logical, and other operators in Python.
Control Flow: Explore decision-making with if-else statements, loops (for and while), and the concept of indentation.
Functions: Understand how to define and use functions in Python for code reusability.
Modules and Packages: Explore how to import and use pre-built modules and packages in Python.

Step 3: Data Structures and Manipulation

Lists: Learn about lists, their properties, and how to manipulate and access elements.
Strings: Understand string manipulation, slicing, formatting, and commonly used string methods.
Tuples: Explore tuples, their immutability, and various operations on them.
Dictionaries: Understand dictionaries, their key-value pairs, and how to manipulate them.
Sets: Learn about sets and their operations.

Step 4: Object-Oriented Programming (OOP)

Classes and Objects: Understand the principles of OOP, define classes, create objects, and use attributes and methods.
Inheritance and Polymorphism: Explore inheritance, overriding methods, and achieving polymorphism.
Encapsulation and Abstraction: Learn about data hiding, encapsulation, and abstract classes.

Step 5: File Handling and Modules

Reading and Writing Files: Understand how to read from and write to files using Python.
Exception Handling: Learn how to handle errors and exceptions using try-except blocks.
Working with Modules: Explore creating and using your own modules, as well as using external modules from the Python Standard Library and third-party packages.

Step 6: Intermediate Concepts

Regular Expressions: Understand how to use regular expressions for pattern matching and text manipulation.
Generators: Explore generators and their benefits for memory-efficient programming.
Decorators: Learn how to use decorators to modify the behavior of functions or classes.

Step 7: Advanced Topics (Optional)

Multithreading and Multiprocessing: Explore concurrent programming with threads and processes.
Database Connectivity: Learn how to connect Python with databases and perform CRUD (Create, Read, Update, Delete) operations.
Web Scraping: Understand how to extract data from websites using libraries like BeautifulSoup or Scrapy.
Web Development: Get an introduction to web frameworks like Django or Flask for building web applications.

Remember that learning Python is an ongoing process, and practice is key. Work on small projects, solve coding challenges, and participate in coding communities to enhance your skills.

Please note that this syllabus is just a suggested roadmap, and you can adjust it based on your preferences and goals.

Once you Learn Python you can apply it in below areas :

Python is a versatile programming language with a wide range of applications. If you’re looking to enhance your skills with Python, here are some areas you can explore:

Web Development: Python is commonly used for web development. Learning web frameworks like Django or Flask can enable you to build dynamic and scalable web applications. Additionally, understanding HTML, CSS, and JavaScript alongside Python can help you create full-stack web solutions.
Data Analysis and Visualization: Python has powerful libraries such as NumPy, Pandas, and Matplotlib that facilitate data analysis and visualization. Mastering these libraries can enable you to manipulate, analyze, and visualize data, making it valuable for data scientists and analysts.
Machine Learning and Artificial Intelligence (AI): Python provides excellent support for machine learning and AI projects. Libraries like scikit-learn, TensorFlow, and PyTorch are widely used for developing and implementing machine learning models. Understanding these libraries and concepts like regression, classification, and neural networks can open doors to AI-related careers.
Scripting and Automation: Python’s simplicity and readability make it an excellent choice for scripting and automation tasks. By learning how to write scripts and automate repetitive tasks using Python, you can significantly improve productivity and efficiency.
Game Development: Python has game development frameworks like Pygame that allow you to create games. By learning these frameworks, you can build interactive 2D games and explore the realm of game development.
Internet of Things (IoT): Python can be used to interact with IoT devices and process sensor data. Understanding how to leverage Python for IoT projects can be valuable for building smart systems and integrating devices.
Desktop Application Development: Python, along with frameworks like Tkinter and PyQt, can be used to create cross-platform desktop applications with graphical user interfaces (GUI). Developing desktop applications can be useful for building tools, utilities, or customized software.
Web Scraping: Python’s libraries, such as BeautifulSoup and Scrapy, enable web scraping, which involves extracting data from websites. Web scraping is used for data collection, analysis, or automation of tasks that require web data extraction.

Remember that these are just a few areas where Python can be applied. The language’s versatility allows it to be used in various domains, so consider exploring areas that align with your interests and career goals.

While learning Python, there are several other technologies that can complement your skills and expand your career opportunities. Here are a few technologies worth considering:

SQL (Structured Query Language): Understanding SQL is essential for working with databases. Python has libraries like SQLAlchemy that facilitate interaction with databases, but having a solid grasp of SQL allows you to efficiently retrieve, manipulate, and analyze data stored in databases.
Cloud Computing Platforms: Familiarize yourself with popular cloud computing platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP). These platforms provide a range of services like cloud storage, compute resources, and machine learning tools. Integrating Python with cloud platforms can help you deploy scalable applications, leverage cloud services, and work with big data.
Docker and Containerization: Containerization technologies like Docker have gained significant popularity. Learning how to containerize applications and deploy them using tools like Docker can enhance your ability to create portable and scalable software solutions.
Version Control Systems: Git is a widely used version control system for managing source code. Understanding Git and using platforms like GitHub or GitLab enables collaboration, code sharing, and version control in your projects. It’s essential for working effectively in software development teams.
Front-End Development: While Python is primarily used for back-end development, having some knowledge of front-end technologies can be beneficial. Learning HTML, CSS, and JavaScript, along with front-end frameworks like React or Angular, allows you to develop full-stack applications and collaborate better with front-end developers.
DevOps Tools: DevOps practices aim to enhance collaboration and automation between software development and operations teams. Familiarize yourself with popular DevOps tools like Jenkins, Ansible, or Kubernetes, as well as concepts like continuous integration and continuous deployment (CI/CD). Python can be used alongside these tools to automate deployment processes and infrastructure management.
Data Streaming and Messaging Systems: Apache Kafka and Apache RabbitMQ are examples of popular messaging and data streaming systems. Understanding how to integrate Python with these systems allows you to build scalable, event-driven applications that handle large volumes of real-time data.
Data Visualization Tools: Python offers various data visualization libraries, such as Matplotlib, Seaborn, and Plotly. However, exploring specialized data visualization tools like Tableau or Power BI can provide additional capabilities for creating interactive and insightful visualizations.

Remember, the choice of additional technologies depends on your specific interests, career goals, and the domain you want to specialize in. Stay updated with industry trends, explore technologies aligned with your projects, and continuously learn and adapt to the evolving IT landscape.

Thanks a lot for reading ,

Happy Learning.