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For different learning styles, goals, and comfort levels, finding a SQL course that matches how you learn is hard. Some learners want theory first. Others want to run queries immediately. And many learners just want proof of effort at the end in the form of a certificate. This list is built with that in mind. A list of free SQL courses, each suited to a different type of learner, so you can stop forcing yourself into the wrong learning format and start learning in a way that actually works for you. From the curious beginner to seasoned professional, this list…

Image by Author   # Introduction  For an LLM engineer, the ecosystem of tools and libraries can feel overwhelming at first. But getting comfortable with the right set of Python libraries will make your work significantly easier. Beyond knowing Python fundamentals, you need to be comfortable with libraries and frameworks that help you build, fine-tune, and deploy LLM applications. In this article, we’ll explore ten Python libraries, tools, and frameworks that will help you with: Accessing and working with foundation models Building LLM-powered applications Implementing retrieval-augmented generation (RAG) Fine-tuning models efficiently Deploying and serving LLMs in production Building and monitoring AI…

AI development is accelerating fast. Advances in hardware, software optimization, and better datasets now allow training runs that once took weeks to finish in hours. A recent update from AI researcher Andrej Karpathy shows this shift clearly: the Nanochat open-source project can now train a GPT-2 model on a single node with 8× NVIDIA H100 GPUs in about two hours, down from three just a month ago. Even more striking, AI agents made 110 code changes in 12 hours, improving validation loss without slowing training. In this article, we look at how self-optimizing AI systems could reshape the way AI…

Image by Author   # Introduction  If you’re building applications with large language models (LLMs), you’ve probably experienced this scenario where you change a prompt, run it a few times, and the output feels better. But is it actually better? Without objective metrics, you are stuck in what the industry now calls “vibe testing,” which means making decisions based on intuition rather than data. The challenge comes from a fundamental characteristic of AI models: uncertainty. Unlike traditional software, where the same input always produces the same output, LLMs can generate different responses to similar prompts. This makes conventional unit testing ineffective…

Having the right certificate can make all the difference. But with so many out there, getting the right one isn’t easy. That’s where Anthropic Academy comes in. Anthropic, the company behind the Claude AI models, has introduced a learning platform through its Skilljar academy that offers structured AI courses designed for building modern AI systems. These courses cover topics like AI fundamentals, prompt engineering, Claude APIs, cloud deployment, and AI agent frameworks. The best part? All of these courses are completely free and offer certificate of completion after finishing the final assessment. This article lists the best Anthropic Academy’s AI courses…

Image by Author   # Introduction  If you are on LinkedIn, X.com, or Reddit, you have probably noticed how many people are now using agentic AI tools to automate parts of their work and even their daily lives. What is more surprising is not just the automation itself, but the fact that many are turning these tools into real income streams. The shift in 2026 is clear. AI is no longer just a chatbot that answers questions. With agentic systems, automation platforms, and coding copilots, individuals are building small systems that handle research, outreach, content, and even product development. You no…

Have you ever wanted faster type checking for Python without slowing down your workflow? Tools like MyPy can catch type errors, but they often feel slow or disconnected from the editor experience. This is where Pyright comes in. Pyright is a standards-based static type checker for Python designed for speed and fast feedback. It runs both as a command-line tool and as a language server, enabling real-time diagnostics while you write code. It integrates closely with Microsoft’s Python tooling and works across editors through the Language Server Protocol (LSP). What is Pyright? Pyright uses a project-based configuration system that defines which files are…

Suppose there is a smart computer in your cell phone. It responds instantly, knows your language, and is completely functional even without the internet. This AI will keep your information confidential on your device. It does not need any additional charge per question. Such is the future that Sarvam Edge is creating in India. Sarvam Edge is a form of AI that takes the form of power to our devices and alters our relationship with technology as we know it. This guide will demonstrate to you what Sarvam Edge is and what it is capable of. You can begin building…

OpenAI is out with a major update, building on its GPT-5 series with the all-new GPT-5.4. Introduced as GPT-5.4 Thinking, the model will also come with a GPT-5.4 Pro version for those seeking “maximum performance” on complicated tasks. Even the base version comes with a plethora of improvements over the outgoing GPT-5.2. These upgrades range across reasoning, coding, and agentic workflows, along with some nifty little features that users are sure to love. For instance, OpenAI says that the GPT-5.4 Thinking will let you adjust the course of its thinking in the middle of a response. This means more appropriate…

Image by Editor   # Introduction  Python decorators are tailor-made solutions that are designed to help simplify complex software logic in a variety of applications, including LLM-based ones. Dealing with LLMs often involves coping with unpredictable, slow—and frequently expensive—third-party APIs, and decorators have a lot to offer for making this task cleaner by wrapping, for instance, API calls with optimized logic. Let’s take a look at five useful Python decorators that will help you optimize your LLM-based applications without noticeable extra burden. The accompanying examples illustrate the syntax and approach to using each decorator. They are sometimes shown without actual LLM…