Arun Prakash M’s Post

Arun Prakash M makes a brilliant point here. Adding on to it on why I think python is a good language to learn. 1. range of use: you can use python for - data science (tons of models are python based) - data engineering (date pipelines pretty much run on python) - devops (almost all infrastructure as code platforms have a python API) - backend. (Django, FastAPI) there are even efforts to make python write frontend code. 2. easy to learn: compared to most languages, python is extremely easy to learn. 3. job opportunities: python has become the de facto in most job requirements. learning it will give you an added advantage. Happy learning!

New Study Reveals 70% of Python Developers Use Virtual Environments for Efficient Coding. Dive into the Data and Enhance Your Python Skills Today! Did you know that 86.6 million websites on the internet are powered by Python? This dynamic and versatile programming language is favored by developers worldwide for its simplicity and readability. But that's not all, Python is also extensively used in scientific computing, data analysis, artificial intelligence, and machine learning. In fact, Python's popularity is soaring in these fields. The number of job postings requiring Python skills has increased by 240% since 2014. Industries such as finance, healthcare, and technology are actively seeking professionals proficient in Python. But why should you care? Well, learning Python opens up a world of opportunities. You can launch a successful career in data science, build innovative applications, or even contribute to cutting-edge research. So, if you're looking to enhance your technical skills or explore exciting career prospects, Python should be at the top of your list. With its extensive libraries, community support, and excellent documentation, mastering Python has never been easier. Are you ready to embark on this transformative journey? Let us know in the comments below which Python applications excite you the most. #PythonProgramming #DataScience #MachineLearning #CareerOpportunities Source: https://lnkd.in/e4Fghk4Q

Why Learn Python? Python is like the Swiss Army knife of programming languages. Python is a popular programming language that is widely used in various industries, including data science, machine learning, web development, artificial intelligence, finance, education, research, security, and many more. Here are some reasons why you should learn Python: Versatility: Python is an extremely versatile language that can be used for a wide range of applications, including data mining, web development, automation scripting, gaming, network development, and more. Ease of Use: Python is easy to read, write, and learn compared to other programming languages. Its simple syntax and efficient coding allow programmers to get up and running quickly. Scalability: Python is highly scalable and can be used for both small and large projects. It is used by some of the world's largest companies and is great for quick and simple prototypes Career Opportunities: Python provides several job opportunities and promises high growth with huge salary prospects. It is used by companies in various industries, and having Python knowledge and skills can open doors to various career opportunities such as software engineer, data scientist, research analyst, and more Active Community: Python has a massive community that can help you in programming errors or issues with the software. You can post your queries in community forums, and community members will address them in real quick time. #python #python3 #programminglanguage #learning

How much Python should I know before jumping into Data Science/Machine Learning? To get started with Data Science, you need zero knowledge of Python. In fact you can build a full fledged Machine Learning system without knowing any Python. But the more important question is, Is this option sustainable for a Data Science career in the longer run? The answer is No. Let us try to understand this. Finally, our goal as a Data Scientist is to build ML systems for the company that is hiring. And the system needs to go to production. For that, you need to use a programming language which is popular and which has good community support. And in Machine Learning, the hands down winner is Python, which has a great amount of community support. You can also do full fledged server side web development using Python. So, coming back to the question, how much Python should I learn? Learn the basics to start with, then get started with Machine Learning and continue learning Python alongside as and when required. Don't wait to become a Master in Python before you can start ML. #avijitroy #machinelearning #python

Yes, you should still learn Python even if you already know R... 📣 Python vs R for Data Science First of all, I think it's a mistake to think of these two as "rival" languages. Think of them as complementary tools instead, and believe me, as a Data Scientist you'll need many in your toolbox. 📈 Although R is specifically designed for statistical analysis, which makes it particularly well-suited for projects that require complex data visualization or detailed statistical analysis. 🌎 Python is generally more versatile, making it suitable for a broader range of data science tasks, including data manipulation, data analysis, machine learning, deep learning, and data visualization. I've been working in Tech for over 6 years, and I can tell you with confidence that most Data Scientists use Python in their day-to-day. ✅ If you already know R, then learn Python. This will open many doors of opportunity in your career. ✅ If you only have time to learn one, then start with Python.

The Importance of Python: Why You Should Learn It! Python is more than just a programming language; it's a powerful tool that can transform your career! Here are some reasons why Python is essential in today’s tech landscape: 1️⃣ Versatility: From web development to data analysis, machine learning, and automation, Python has a wide range of applications. What’s your favorite use case? 2️⃣ Simplicity: Python's clear syntax and readability make it an excellent choice for beginners. Have you tried learning Python? Share your experience! 3️⃣ Strong Community Support: With a vast community of developers, you’ll always find help and resources. Which Python community or resource has been the most helpful for you? 4️⃣ In-Demand Skills: Companies are actively seeking Python developers. It's a skill that can open doors to new job opportunities! What job role in tech are you aiming for? 5️⃣ Data Science & AI: Python is the go-to language for data scientists and AI professionals. Are you interested in data science or machine learning? Let’s discuss! Comment below with your favorite Python project or a Python-related question you have. Let’s learn from each other! credits: Respective owner #Python #Coding #TechSkills #DataScience #MachineLearning #CareerDevelopment #LearnPython

Why learn Python? 🐍 Python is one of the most versatile and widely-used languages in tech today, making it a top choice for anyone looking to upskill. Its simplicity makes it beginner-friendly, while its powerful libraries make it indispensable in fields like data science, machine learning, web development, and automation. With Python skills in high demand across industries like finance, healthcare, and artificial intelligence, investing time in learning this language can open doors to some of the best opportunities in tech. Whether you’re just starting out or looking to pivot, Python is a smart career move! #Python #TechSkills #LearningAndDevelopment

What is the future of Python? 👍 The future of Python looks incredibly promising, and it is expected to play an increasingly vital role in various fields. Python's simplicity, versatility, and growing ecosystem make it one of the most widely used and powerful programming languages today. Below are several reasons why Python's future is bright: 👍1. Data Science and Machine Learning: Python is a dominant language in data science, machine learning (ML), artificial intelligence (AI), and big data. Libraries like TensorFlow, PyTorch, Pandas, and Scikit-learn make it the go-to choice for data scientists and machine learning engineers. As AI and data-driven industries continue to grow, Python's usage in these fields will only increase. 👍2. Web Development: Python's frameworks such as Django and Flask are widely used for web development, making it easier to build scalable, secure, and fast web applications. The simplicity and flexibility of these frameworks ensure that Python will remain a strong choice for web developers. 👍3. Automation and Scripting: Python excels at automation, task scripting, and system administration due to its simple syntax and powerful standard library. From automating repetitive tasks to complex network automation, Python is widely used in DevOps and IT operations, and this trend is expected to continue. 👍4. Expansion of Libraries and Frameworks: The Python ecosystem is continually expanding, with new libraries and frameworks being developed in various domains, such as scientific computing, natural language processing (NLP), bioinformatics, and robotics. As more developers contribute to the open-source community, Python will see even broader applications. 👍5. Strong Community Support: Python has a massive and active community, which helps in continuous improvement of the language and its libraries. The availability of extensive documentation, tutorials, and community-driven forums makes Python accessible for beginners and professionals alike. This strong community support will ensure Python's longevity. 👍6. IoT (Internet of Things): Python is gaining traction in the IoT space due to its compatibility with low-power devices and microcontrollers. Frameworks like MicroPython and CircuitPython allow developers to use Python for embedded systems and IoT applications, which will become more significant as IoT continues to grow. #programmingmemes #programming #coding #programmer #python #code #webdeveloper #programmingisfun #developerlife #programmers #java #webdevelopment #developer #softwaredeveloper #computerprogramming #cprogramming #programmingquotes #tech #php #computer #development #programminghumor #programmingofficial #javaprogramming #programminghumour #programmingstudents #programmingcontest #computerscience #machinelearning #softwareengineer

Many people ask me, "Which tool should I learn?" And my answer often includes Python. This versatile language powers numerous specialized roles in today’s tech landscape, each demanding unique skills but grounded in Python fundamentals. Let’s explore some of these roles: 𝐖𝐞𝐛 𝐒𝐜𝐫𝐚𝐩𝐞𝐫 – Extracts data from websites for use in industries like finance, e-commerce, and research. 𝐏𝐲𝐭𝐡𝐨𝐧 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 – Specializes in building Python-based applications, automations, and integrations. 𝐅𝐮𝐥𝐥 𝐒𝐭𝐚𝐜𝐤 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 – Uses Python on the backend (Django/Flask) to support complete web applications. 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐭 – Utilizes Python libraries (like Pandas, Matplotlib) to analyze, visualize, and interpret data trends. 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 – Creates and manages data pipelines, ETL processes, and database interactions. 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 – Designs and trains models using libraries such as Scikit-Learn, TensorFlow, and PyTorch. 𝐀𝐈 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡𝐞𝐫 – Advances artificial intelligence solutions, leveraging Python’s deep learning libraries. 𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 – Develops backend systems, builds APIs, and automates workflows using Python. 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 – Automates repetitive tasks and testing processes with Python scripts. 𝐃𝐞𝐯𝐎𝐩𝐬 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 – Writes Python scripts to manage infrastructure, CI/CD pipelines, and automate server tasks. 𝐆𝐚𝐦𝐞 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 – Uses Python (often with PyGame) to build game logic and interactive components. 𝐒𝐜𝐫𝐢𝐩𝐭𝐢𝐧𝐠 𝐚𝐧𝐝 𝐓𝐨𝐨𝐥𝐢𝐧𝐠 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 – Creates custom tools to streamline workflows and productivity. 𝐂𝐲𝐛𝐞𝐫𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐀𝐧𝐚𝐥𝐲𝐬𝐭 – Writes scripts for threat detection, security automation, and forensic analysis. 𝐅𝐢𝐧𝐚𝐧𝐜𝐢𝐚𝐥 𝐀𝐧𝐚𝐥𝐲𝐬𝐭 – Builds quantitative models, automates trading algorithms, and analyzes financial data. 𝐁𝐢𝐨𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐜𝐬 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐬𝐭 – Analyzes biological data and builds models for genomics research using Python libraries. Each of these roles showcases Python’s adaptability. Whether it’s analytics, machine learning, automation, or web development, Python opens doors to a diverse array of impactful careers. If you’re considering which tool to dive into, Python is a versatile, future-proof choice. I see a big need of an online marketplace where specialized people in more than 500 fields of IT and emerging technologies should train future talent #PythonRoles #PythonCareers #TechIndustry #DataScience #WebDevelopment #Mentors #Mentees #Emergingtechnologies