Guido van Rossum developed Python, a high-level, adaptable programming language, in 1989. Because of its readability, ease of use, and numerous uses in fields including web development, data science, machine learning, and automation, it has grown to become one of the most widely used languages.
Python is a great option for both novice and seasoned developers due to its simple syntax and large library. Its significant industrial demand, active community, and integration with technologies like Visual Studio and Microsoft Azure further add to its allure.
Gaining knowledge of Python may lead to many job options and provide you a strong foundation in the ever changing tech industry.
Our journey began by mastering basic web development skills - HTML, CSS, and JavaScript. From there, you experimented with various programming languages until you found one that met all our requirements.
During that time, C, Java, and Pascal (the language taught in first-year class at school) came and went until Python took hold for good - you gave it a go. You studied some more before ultimately choosing it to become our standard programming language.
What Is Python?
Python is an all-purpose programming language; unlike its competitors, JavaScript and HTML are limited in their applications solely for web development projects.
Since its invention over 30 years ago, Python has quickly become one of the worlds most beloved and used programming languages.
Why Learn Python?
Learning any new programming language can be daunting and time-consuming if left to your resources and guidance alone; it can also become enjoyable with proper direction! When given adequate advice, it can even turn out to be fun!
Guido van Rossum created Python on December 3rd, 1989, under his design philosophy: "This is the only way you know to do it, and that is why it works." Python is a high-level general-purpose interpreted programming language primarily using english keywords for object-oriented programming tasks.
Why learn Python, especially if you are considering a tech career or want to increase your skill set?
Versatility Of Python
Pythons versatility ensures it remains relevant in an ever-evolving job market, offering endless potential.
Career Prospects
Pythons widespread appeal can provide professional developers with many career prospects; companies like Microsoft actively recruit Python programmers.
Community Assistance
Its Python boasts an active and large community. Novices or experts will find plenty of support online; learning Python becomes much simpler thanks to such an abundant body of helpers!
Learnability
Python is among the simplest programming languages to pick up quickly; no complicated rules and syntax must be learned before creating practical applications.
Python Has An Extremely Straightforward Syntax
Python offers a highly user-friendly language experience for newcomers in tech. While its simple syntax may initially not appeal to you, once you read its detailed breakdown, youll soon see its appeal and take part.
Python is one of the easiest languages to learn. It uses fewer lines of code to complete any given task, making its fundamentals easy to grasp quickly. As an interpreted programming language, it doesnt require compilers for its code to run and write itself!
Python Is Beginner-Friendly
Why learn Python? This beginner-friendly programming language makes an excellent starting point if youre new to programming.
Learning another foreign language may initially seem intimidating; fortunately, Python features English syntax while compact and user-friendly, so knowing it should pose fewer obstacles for new coders than most languages would.
Pythons interpretive nature makes it simple for newcomers and experienced coders alike to pick up, with instant run-time for your code.
This saves both time and energy when learning or developing code - both crucial factors when learning a programming language for beginners.
Python Is Versatile
Python can be applied in numerous fields and industries ranging from data science, software engineering, mobile apps, and machine learning to artificial intelligence & more.
Due to over 125,000 libraries - prewritten codes are explicitly written in an easy language that anyone can utilize - its uses span from data analysis and programming applications through mobile phone apps for machine learning & artificial intelligence to environmental studies & more.
Once learned, the fundamentals will enable users to utilize large amounts of code other programmers efficiently write!
Python is a highly flexible programming language that can easily integrate with many other programming languages - Jython integrates Python and Java, while CPython handles C.
Furthermore, its use across platforms such as Windows, Linux, or MacOS makes this choice even more flexible.
Python Developer Roles Are In High Demand
Many large corporations such as Dropbox and Netflix rely on Python, with Google creating its style guide for this language.
Furthermore, positions as Python developers tend to be lucrative: Indeed* reports an average annual salary for Python programmers of $108,391, making this language one of the four most sought-after languages: Ruby ($120.174), C++ (114k) and JavaScript ($111.623).
StackOverflow indicates they may even earn good salaries even without extensive experience!
Python Has An Active Community
After you complete your degree or bootcamp, there must be an extensive community for you to connect with, particularly after graduation or bootcamp completion.
Python boasts one of the worlds second-largest communities on GitHub with 1.5 Million repositories as evidence; plus, users create meetup groups worldwide through community forums where junior developers discuss everything from software development and workflow to workflow practices and more!
Python Is The Fastest-Growing Programming Language
Python is one of the fastest-growing programming languages, and its popularity and growth rate are undeniable. According to PYPL Popularity of Programming Language Index data, Python is currently the most searched programming language online - this trend does not appear likely to end any time soon - according to Stack Overflow data, Python is fast emerging as one of the fastest expanding coding languages!
TIOBE awarded Python the 2020 Programming Language of the Year Award due to its vast popularity among other programming languages.
Python has quickly become one of the go-to languages in data science; machine learning, data modeling, and AI continue to emerge and require Python skills, so its increasing adoption makes a lot of sense if your goal is entering programming as a profession or starting learning to program now!
Python For Beginners: 3 Top Uses In Data Science
Data Science
Python has long been considered the go-to programming language in data science due to its time-saving libraries and ability to handle repetitive tasks effectively.
With more and more people flocking to online communities in their pursuit of data, this popularity only continues.
Web Development
Pythons flexibility simplifies web development with Django (a popular framework). Django simplifies building both front-end and back-end functionality for clients and back-end developers, which are essential features.
Large corporations like Google and YouTube rely heavily on Python web development solutions as part of their digital infrastructures.
App Development
Python is an ideal language to begin app development with due to the minimal time and effort necessary for prototyping it, its cross-platform support, real-time testing frameworks, and robust frameworks proving particularly popular with fast-growing blockchain and gaming apps development industries.
Python: 3 Ways To Get Started
There are various paths to learning Python, from bootcamps and traditional degrees to self-teaching or independently studying it.
Each option has advantages based on your needs, preferences, and limitations as an individual coder; your route will depend heavily upon your career goals as different avenues offer more chances to combine Python with other languages or skills.
Data Analytics Bootcamps
Bootcamps provide intensive instruction in multiple programming languages over an intensive three to six-month course period, making learning how to program flexible enough for those juggling other responsibilities while studying programming simultaneously.
They focus on teaching analytical fundamentals like pivot tables and VBA programs and front-end web tools like HTML/JAVAScript charts, which all aid students ability to solve and analyze complex problems effectively.
The data analysis and visualization boot camp teaches its students Python basics and works with numpy and pandas libraries for data-focused applications.
Students learn to transform extensive data sets into insights they can use for strategic advantage within organizations or individually - they even come away with professional portfolios as proof!
Are You Wondering the Benefits of Attending a Data Analytics Boot Camp
A bootcamp devoted to Python could be an excellent choice for individuals interested in entering data science and analytics fields.
With Python increasingly wide range utilized across this industry, learning this script provides a great entryway.
Python provides an effective means for sharpening data analyst skills. A data analyst must possess multiple abilities to analyze complex data, recognize trends, communicate insights clearly, work effectively within teams, and communicate well.
Graduates from these programs dont just become data analysts - they may become business analysts, software developers, or data scientists!
Traditional Studies
Free Learning
Python Is An Ideal Programming Language For Beginners
Beginners tend to like Python because of its ease of use and readability; Developers appreciate its ability to effectively manage complex projects; Microsoft has implemented this language in their ecosystem as well!
Data Science And Machine Learning
Python has long been considered the go-to choice for machine learning and data science applications, offering great libraries like NumPy Pandas and TensorFlow for manipulating data and building AI applications
Microsoft's Azures cloud platform also has strong support for Python, so developers can take full advantage of its potential for data analytics, AI analytics and machine learning applications alike
Website Development
Python has quickly become one of the go-to languages for web development thanks to the Django and Flask frameworks.
At the same time, Microsoft Azure App Service makes it easy for developers to deploy and manage Python web apps.
Automation With Python
Python is a fast-paced programming language with an easy-to-understand syntax, making Microsoft's support for PowerShell, Azure services, and other products a valuable asset in streamlining automation and scripting processes
Game Development
The Python library Pygame has gained increasing attention as an effective game stack development solution on Windows systems, thanks to Microsofts support for game development for this OS as evidence of their commitment to Python and their Visual Studio Code Python game development expansion also shows this.
Microsofts Commitment To Python
Microsoft is taking serious steps in its commitment to supporting Python in its products and community. There have been many projects aimed at increasing the use of Python internally.
Python Tools For Visual Studio
Microsofts powerful Python IDE (Visual Studio) makes using Python in enterprises rigorous for developers.
Python Tools for Visual Studio (PTVS) is a unique integrated development environment (IDE), which gives Python developers increased productivity when working with Microsoft Visual Studio IDE - the top featured IDE available today one of the characters
The open-source framework PTVS leverages this capability for Python development applications by quickly testing and debugging code in its known environment.
Python Tools for Visual Studio has many unique features that set it apart.
- Integrated Development: Environment PTVS provides a complete Python environment integrated in Visual Studio so you can write, edit, and maintain Python code along with other projects in its domain
- Python Language: Support from PTVS We provide robust Python support from PTVS, including code completion, analysis, and navigation to help write clean code.
- Communication Windows: One of the unique characteristics of PTVSs is their communication windows. Python REPL and IPython RePL can be used, which provide opportunities for rapid experimentation and observation of interactions.
- Debugger: Powerful and Easy, Python Testing is an extensive yet user-friendly debugger in the Visual Studio suite that includes features like breakpoints and variable tracking, making it much easier to troubleshoot Python code.
- Program Management: Visual Studio Python makes creating, managing, and building solutions and services easier than ever - now you have the tools to create complex Python apps with ease and efficiency!
- IntelliSense: PTVS provides intelligent code completion that will help you write Python faster and with fewer errors. It detects issues related to your codes and suggests appropriate suggestions as you type.
- Interactive Data Visualization: You can easily create interactive plots and data visualizations using Matplotlib or other visualization tools.
- Unit Testing: PTVS integrates popular Python testing frameworks such as unittest and testing to create, execute, and edit unit tests in your IDE environment. In this case, unit tests can be written, executed, or edited more easily.
- Web Development: PTVS provides web development support for Python. With their simple development environment and support for popular Python frameworks like Django or Flask, building web applications is easy with these supports.
- Integration With Microsoft Azure: PTVS integrates seamlessly with Microsoft Azure for easy development and deployment of Python apps in the cloud.
- Third-Party Package Management: Through virtual environments and pip, PTVS makes it easy to manage third-party Python packages, dependencies, and third-party sources and tools
- Refactoring: Python Technical Verification Services ptvs provides code refactoring to enhance the quality and look of python code.
- Customization and Extensibility: Like Visual Studio, PTVS enables users to customize and extend their environment with various add-ons.
Python Tools for Visual Studio (PTVS) provides a high-performance environment for developers using Visual Studio, especially for web development or data science projects involving Python development
Additionally, it simplifies Python development and provides a unified workspace across programming languages.
Azure Machine Learning
Azure Machine Learning provides an efficient way to develop, train and use machine learning models written in Python to build and deploy AI applications.
Microsoft designed the project as an extensible and scalable machine learning AI solution platform for innovation, training programs and applications.
Azure Machine Learning was built to accelerate and simplify every step of machine learning, from model building, data preparation, to monitoring and deployment
Data scientists, software developers and enterprises alike can use its services and tools that enable artificial intelligence and machine learning to provide more powerful decision-making and insights
Azure Machine Learning has many special characteristics that make it a valuable tool, such as its user-friendly interface for creating machine learning pipelines and support for multiple programming experience languages, frameworks, and features others
Azure Machine Learning simplifies its processes to make machine learning experiments faster and more efficient for users, and enables users to quickly and effectively test machine learning models
Additionally, its seamless integration with tools like Jupyter Notebooks gives data scientists access to known environments that fully leverage the Azures security infrastructure
Microsoft Learn
The interactive and dynamic online learning platform created by Microsoft, known as "Microsoft Learn," offers numerous free resources, including Python classes.
Microsoft Learn promotes continuous learning to make Python more approachable to all, with free and easily accessible resources available to learn about many products and technologies created by the software giant.
Microsoft learn offers modules, courses, tutorials, and labs tailored for users at every skill level - everything you need to acquire new abilities! It has an abundance of content designed to assist learners.
Microsoft Learns learn-by-doing approach stands out among its many outstanding characteristics, prioritizing practical experience through fundamental world exercises and scenarios to put the knowledge learned into practice.
This platform benefits professionals, IT enthusiasts, and developers seeking knowledge about Microsoft cloud services, development tools, and applications.
Python Support in Microsoft Azure
Microsoft Azure offers an integrated Python platform. Azure makes this integration effortless, whether used to develop web apps, manage cloud infrastructure, or implement machine-learning models.
Microsoft Azure provides an array of Python-related services. Azure provides an ideal environment for developing, deploying, and managing Python applications; its platform also boasts numerous services and tools designed to make this programming language seamless in web apps, data science, or machine-learning models.
Azure Machine Learning makes AI-driven Python solutions simple to develop and deploy quickly and cost-effectively.
At the same time, Azure Functions allows developers to build serverless Python apps. Azure Notebooks, Databricks, and Databricks offer flexible environments for collaborative data processing and analysis, perfect for Python development companies looking for robust cloud-native solutions with scale.
Which Python Libraries Should You Use for Data Science?
Python offers an impressive collection of libraries and frameworks that simplify data analysis, visualization, and manipulation.
Here are the top libraries used in data science!
- NumPy: IT is a Python library for scientific and numerical computing, supports large multidimensional arrays and includes math functions that operate directly upon them.
- Pandas: Pandas is an intuitive data structure (DataFrame or Series) for efficiently handling structured data for cleansing, exploring, and transformation purposes. It makes your life much simpler by streamlining this process!
- Matplotlib: (pronounced mah-plot-lib) is a Python library designed for creating static, animated, and interactive visualizations in graphs, charts, and figures.
- Seaborn's: foundation lies within Matplotlib; with this tools enhanced interface and attractive and informative statistics graphics creation features, Seaborn makes for an exceptional solution when conducting data and statistical analyses. It makes an invaluable asset in terms of data analysis.
- Scikit Learn: One of the premier Python machine learning libraries, Scikit Learn provides simple yet efficient and robust data modeling and analysis tools, including classification, regression, and clustering capabilities.
- TensorFlow: developed by Google as an open machine learning framework, has proven particularly popular with neural network and deep learning applications.
- Keras: Keras is an intuitive neural network API running on TensorFlow or Microsoft Cognitive Toolkit and makes deep learning prototyping much more straightforward.
- PyTorch: PyTorch, an open-source machine learning library designed for deep learning applications, excels at dynamic computation graphs known for their flexibility and the support provided by its vibrant community.
- Statistics Models: is a Python library designed to estimate and interpret statistical models. With functions for time series analysis and linear and nonlinear model representation, Statsmodels helps assess and diagnose these statistical models more precisely than ever.
- XGBoost: is an optimized gradient-boosting library widely utilized in supervised learning applications. It is known for its speedy performance and fast computing speed.
- LightGBM: LightGBM is an efficient gradient boosting framework tailored explicitly for Kaggle and machine-learning competitions, such as those organized by Machine Learning Network.
- NLT: Natural Language Toolkit is a library designed to allow users to manage data related to human languages, with accessible interfaces for tasks like tokenization, stemming, and tagging capabilities.
- Beautiful Soup: is a web scraping library that simplifies data extraction from web pages by parsing HTML documents and XML files.
- Dask: Dask is an open and free parallel computing tool providing data scientists with a means of adapting their workflows for larger datasets or distributed computing environments.
- Bokeh: Bokeh is an interactive visualization library designed for web pages that enables the interactive display of data on an interactive dashboard or plot. This tool helps create engaging dashboards and stories on websites.
These Python data science libraries cover an array of tasks in data science, from data analysis and manipulation to machine learning and deep learning, etc.
Your project requirements will determine which libraries to utilize; nonetheless, having knowledge about Python data science libraries for data scientists or analysts is indispensable.
Conclusion
Microsofts Python support isnt just a passing trend. This investment in an indispensable tech language stands the test of time.
It helps ensure its presence across many tech fields. Learning Python gives you all the required skills and knowledge to thrive in our technology-driven society - an advantage that Microsoft highlights with its dedication towards it, making it suitable for beginners and experienced developers looking to hone their technical abilities further.
If you aim to expand and strengthen them further, add Python as another weapon against technical skills degradation.
