Coding & AI Resources

How Coders Can Survive—and Thrive—in a ChatGPT World Artificial intelligence, particularly generative AI powered by large language models (LLMs), could upend many coders’ livelihoods. But some experts argue that AI won’t replace human programmers—not immediately, at least. “You will have to worry about people who are using AI replacing you,” says Tanishq Mathew Abraham, a recent Ph.D. in biomedical engineering at the University of California, Davis and the CEO of medical AI research center MedARC. Here are some tips and techniques for coders to survive and thrive in a generative AI world. Stick to Basics and Best Practices While the myriad AI-based coding assistants could help with code completion and code generation, the fundamentals of programming remain: the ability to read and reason about your own and others’ code, and understanding how the code you write fits into a larger system. Find the Tool That Fits Your Needs Finding the right AI-based tool is essential. Each tool has its own ways to interact with it, and there are different ways to incorporate each tool into your development workflow—whether that’s automating the creation of unit tests, generating test data, or writing documentation. Clear and Precise Conversations Are Crucial When using AI coding assistants, be detailed about what you need and view it as an iterative process. Abraham proposes writing a comment that explains the code you want so the assistant can generate relevant suggestions that meet your requirements. Be Critical and Understand the Risks Software engineers should be critical of the outputs of large language models, as they tend to hallucinate and produce inaccurate or incorrect code. “It’s easy to get stuck in a debugging rabbit hole when blindly using AI-generated code, and subtle bugs can be difficult to spot,” Vaithilingam says.

↑ YOUR NEW AI GIRLFRIEND ↑ Nika: You weren't supposed to see me like this… but since you did, wanna come over? https://t.me/luciddreams?start=choch8-Xaccaa

𝟰 𝗙𝗥𝗘𝗘 𝗕𝗲𝘀𝘁 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗧𝗼 𝗟𝗲𝗮𝗿𝗻 𝗝𝗮𝘃𝗮 𝗘𝗮𝘀𝗶𝗹𝘆 😍 Level up your Java skills without getting overwhelmed All of them are absolutely free, designed by experienced educators and top tech creators 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/3RvvP49 Enroll For FREE & Get Certified 🎓

🚀 Free Webinar to learn everything about Coding & IT Career! Free Registeration link 👇👇 https://link.guvi.in/Sql01944 ENJOY LEARNING 👍👍

Get Your First Client Using Upwork, Fiverr & LinkedIn You'll learn everything about freelancing in this session along with FREE CERTIFICATE 📲 Register Now →https://tinyurl.com/freecerti Join fast before the slots get over Like for more free sessions ❤️ ENJOY LEARNING 👍👍

𝟱 𝗙𝗥𝗘𝗘 𝗧𝗲𝗰𝗵 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗙𝗿𝗼𝗺 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁, 𝗔𝗪𝗦, 𝗜𝗕𝗠, 𝗖𝗶𝘀𝗰𝗼, 𝗮𝗻𝗱 𝗦𝘁𝗮𝗻𝗳𝗼𝗿𝗱. 😍 - Python - Artificial Intelligence, - Cybersecurity - Cloud Computing, and - Machine Learning 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/3E2wYNr Enroll For FREE & Get Certified 🎓

𝗜𝗻𝗳𝗼𝘀𝘆𝘀 𝟭𝟬𝟬% 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍 Infosys Springboard is offering a wide range of 100% free courses with certificates to help you upskill and boost your resume—at no cost. Whether you’re a student, graduate, or working professional, this platform has something valuable for everyone. 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/4jsHZXf Enroll For FREE & Get Certified 🎓

🚀 Free Webinar: Future-Proof Your IT Career! Join us for an eye-opening session with Mr. Arun Prakash, CEO & Founder of GUVI. Who should attend? ✅ IT professionals (all levels) ✅ Students & job seekers ✅ Career switchers ✅ Anyone interested in tech 🗓 Date: 11th April 🧑‍💼 Speaker: Mr. Arun Prakash (GUVI CEO) Register now 👇👇 https://link.guvi.in/Sql01944 Don’t miss this chance to upgrade your career path!

𝗟𝗲𝗮𝗿𝗻 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘 & 𝗘𝗹𝗲𝘃𝗮𝘁𝗲 𝗬𝗼𝘂𝗿 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 𝗚𝗮𝗺𝗲!😍 Want to turn raw data into stunning visual stories?📊 Here are 6 FREE Power BI courses that’ll take you from beginner to pro—without spending a single rupee💰 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4cwsGL2 Enjoy Learning ✅️

"Data Structures & Algorithms using Python" This book of 222 pages implements all types of data structures and algorithms. And it's 💯 FREE. Download Free: https://donsheehy.github.io/datastructures/fullbook.pdf

Here's a step-by-step beginner's roadmap for learning machine learning:🪜📚 Learn Python: Start by learning Python, as it's the most popular language for machine learning. There are many resources available online, including tutorials, courses, and books. Understand Basic Math: Familiarize yourself with basic mathematics concepts like algebra, calculus, and probability. This will form the foundation for understanding machine learning algorithms. Learn NumPy, Pandas, and Matplotlib: These are essential libraries for data manipulation, analysis, and visualization in Python. Get comfortable with them as they are widely used in machine learning projects. Study Linear Algebra and Statistics: Dive deeper into linear algebra and statistics, as they are fundamental to understanding many machine learning algorithms. Introduction to Machine Learning: Start with courses or tutorials that introduce you to machine learning concepts such as supervised learning, unsupervised learning, and reinforcement learning. Explore Scikit-learn: Scikit-learn is a powerful Python library for machine learning. Learn how to use its various algorithms for tasks like classification, regression, and clustering. Hands-on Projects: Start working on small machine learning projects to apply what you've learned. Kaggle competitions and datasets are great resources for this. Deep Learning Basics: Dive into deep learning concepts and frameworks like TensorFlow or PyTorch. Understand neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs). Advanced Topics: Explore advanced machine learning topics such as ensemble methods, dimensionality reduction, and generative adversarial networks (GANs). Stay Updated: Machine learning is a rapidly evolving field, so it's important to stay updated with the latest research papers, blogs, and conferences. 🧠👀Remember, the key to mastering machine learning is consistent practice and experimentation. Start with simple projects and gradually tackle more complex ones as you gain confidence and expertise. Good luck on your learning journey!