Best GitHub Copilot Training for Employees
A DataCamp guide comparing GitHub Copilot training options for engineering teams, with published list prices verified October 30, 2026. DataCamp sells some of the training it lists.
29 free resources on this topic. Everything here is free and hand-picked. You can also search within this topic.
A DataCamp guide comparing GitHub Copilot training options for engineering teams, with published list prices verified October 30, 2026. DataCamp sells some of the training it lists.
Google announcement of the Connected Apps Platform for building and managing apps that work inside Gemini and Search; developer access is through a preview sign-up.
Antonello Fratepietro explains "System-One" decision models that return calibrated probabilities over fixed outcomes, covering readout heads, soft-label calibration, batched serving and probing of TypeSafe's Jev.
A developer blog post announcing that Meta is removing the Access Verification step from the Tech Provider onboarding flow, meaning developers who build apps that access client business data no longer submit a separate business review.
An open-source, MIT-licensed SDK from Microsoft for running untrusted code — such as model output, plugins, and tools — in sandboxed containers on Windows, Linux, and macOS. It provides multiple containment backends, from OS-native process sandboxes to full virtual machines, behind a unified containment model, with policy-driven controls for filesystem, network, and UI access, and Rust, .NET, and Node SDKs.
Chrome's documentation for WebMCP, a proposed web standard that lets websites expose structured tools to AI agents and assistants directly from the browser, so agents can act on a site through defined interfaces instead of simulating clicks.
NVIDIA's technical reference for continuous in-silicon monitoring of AI agents: a safety enforcement layer spanning software and hardware that watches agent behavior at the chip level, aimed at securing agents running in production.
Findings from JetBrains' Developer Ecosystem Survey 2026 of more than 15,000 professional developers: 90% used AI coding agents at work at least weekly as of mid-2026, and 68% used them daily. The report tracks how agents are carving out a place in developers' toolkits.
VentureBeat reports that developers at OpenAI's DevDay described model safeguards flagging routine aerospace, robotics and security work as risky — costing hours, disrupting workflows, and pushing some tasks to other models — as OpenAI tries to reduce harmless refusals while tightening safeguards on more capable models.
Google Cloud's overview of 10+ AI tools with free usage tiers, from video and vision AI to app building. Requires a Google Cloud account; usage past free limits is billed.
LeadDev feature on software developers who refuse to use AI tools, even when it costs them clients, job offers and career progress.
Why I recommend it: A set of personal stories, not a survey — useful for understanding the trade-offs, not how common this is.
A September 9, 2025 blog post saying Veracode's research found security flaws in 45% of AI-generated code it tested, and giving advice on checking AI-written code before shipping it.
Why I recommend it: Veracode sells code-security scanning, so it benefits from this finding. The 45% figure comes from its own tests, not independent research. The advice to review AI code still holds.
A small, recurring in-person meetup for developers, tinkerers, and anyone building something technical — AI, cybersecurity, full-stack development, Linux/macOS, shell scripting, Git, and more.
From the site: There's almost nowhere left locally to just show up and work alongside other tech people in person. This is that: a small, recurring meetup for developers, tinkerers, and anyone building something technical, AI, cybersecurity, full-stack development, Linux/macOS, shell scripting, Git, or anything in
Details: Joining the Meetup group is free. Individual events may mention venue costs, but the group itself has no paywall.
A free hackathon to build across Amazon devices and shape what comes next, hosted on Devpost.
From the site: Build across Amazon Devices and shape what's next.
Details: Free to enter. Read the rules on what rights you keep in what you build before you commit a weekend to it.
A free global AI hackathon to build on open infrastructure, hosted on Devpost with Nebius and NVIDIA.
From the site: Build the next frontier of AI on open infrastructure
Details: Free to enter, and a decent excuse to try GPU infrastructure you would not normally pay for. Check what compute credits the organizers hand out.
A free Google Cloud OnAir session on CodeMender, an AI agent that scans, verifies and fixes software vulnerabilities with developer review.
From the site: Discover CodeMender: the AI agent that autonomously scans, verifies, and fixes software vulnerabilities at machine speed, enabling rapid remediation with complete developer control.
Details: Free to attend, but you need to sign in with a Google or email account to register. It is Google presenting Google's own product.
An open-source, self-hosted search engine that queries other engines without tracking you or building a profile. AGPL licensed.
From the site: SearXNG is a free internet metasearch engine which aggregates results from various search services and databases. Users are neither tracked nor profiled. - searxng/searxng
Why I recommend it: Useful if you research employers a lot and would rather not have that history tied to an account.
An open-source drop-in replacement for the OpenAI API that runs models on your own hardware, including CPU-only machines. MIT licensed.
From the site: LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required. - mudler/LocalAI
Why I recommend it: Point existing code at your own server instead of a paid API — no code changes beyond the address.
An open-source tool that converts PDFs, Word files and scans into clean structured text for AI use, running locally. MIT licensed.
From the site: Get your documents ready for gen AI. Contribute to docling-project/docling development by creating an account on GitHub.
Why I recommend it: The unglamorous step that makes everything else work: getting your PDFs into text without a paid converter.
An open-source Python framework for connecting AI models to your own documents and data. MIT licensed.
From the site: LlamaIndex is the document processing platform for AI - run-llama/llama_index
Why I recommend it: For when you want to build something on your own files rather than use a finished app. Expect to write code.
OpenAI's open-source speech recognition model and command-line tool, free to download and run on your own machine. MIT licensed.
From the site: Robust Speech Recognition via Large-Scale Weak Supervision - openai/whisper
Why I recommend it: The original. Slower than whisper.cpp on a laptop, but the reference version and simple to install with Python.
A fast, dependency-light rewrite of OpenAI's Whisper speech-to-text that runs on ordinary laptop hardware, including CPU only. MIT licensed.
From the site: Port of OpenAI's Whisper model in C/C++. Contribute to ggml-org/whisper.cpp development by creating an account on GitHub.
Why I recommend it: Transcribe interviews or your own practice answers privately, without paying a per-minute transcription service.
An open-source AI coding assistant that works in your terminal on a real git repository, making commits as it goes. Apache 2.0 licensed.
From the site: aider is AI pair programming in your terminal. Contribute to Aider-AI/aider development by creating an account on GitHub.
Why I recommend it: It edits real files and commits them, so work on a branch. The tool is free; the model you connect it to is not.
An open-source coding assistant for VS Code and JetBrains that you point at any model, including one running locally. Apache 2.0 licensed.
From the site: open-source coding agent. Contribute to continuedev/continue development by creating an account on GitHub.
Why I recommend it: A free alternative to paid coding assistants if you already run a local model. Slower, but it costs nothing per keystroke.
An open-source platform for building and running AI apps and agents, with a hosted option and a full self-hosted Docker install.
From the site: Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without ...
Why I recommend it: More structure than a chat window: prompts, data and logs kept in one place. Start with their Docker install and one small app.
An open-source drag-and-drop builder for chatbots and AI workflows you can run yourself and embed on a site. Apache 2.0 licensed.
From the site: Build AI Agents, Visually. Contribute to FlowiseAI/Flowise development by creating an account on GitHub.
Why I recommend it: The quickest way to put a working chatbot on your own site without a subscription. You still pay whatever model you point it at.
An open-source visual builder for AI workflows and agents — drag components together, then export the flow as an API. MIT licensed.
From the site: Langflow is a powerful tool for building and deploying AI-powered agents and workflows. - langflow-ai/langflow
Why I recommend it: Useful for seeing what an AI 'agent' actually is: a chain of steps you can look at, not magic.
A self-hosted, open-source chat interface for local or hosted models — chat history, documents, multiple users. Works on top of Ollama or any OpenAI-compatible API.
From the site: User-friendly AI Interface (Supports Ollama, OpenAI API, ...) - open-webui/open-webui
Why I recommend it: If you like the ChatGPT window but not the subscription, this is that window running on your own machine.
Open-source software that downloads and runs open AI models on your own computer, with a single command and an OpenAI-compatible local API. MIT licensed.
From the site: Ollama is the easiest way to automate your work using open models, while keeping your data safe.
Why I recommend it: The easiest honest way to use AI privately — nothing you type leaves your machine. Start with a small model before you judge the speed.