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Learn about the latest technologies from fellow newline community members!

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  • React
  • Angular
  • Vue
  • Svelte
  • NextJS
  • Redux
  • Apollo
  • Storybook
  • D3
  • Testing Library
  • JavaScript
  • TypeScript
  • Node.js
  • Deno
  • Rust
  • Python
  • GraphQL
NEW

What Is an AI Application? Examples, Patterns, and Use Cases

AI applications come in three broad shapes: single-call LLM solutions, workflow-based automations, and agentic systems. Each one balances cost, autonomy, and complexity in its own way. Pick the wrong one and the project stalls. In our experience, the model is rarely the culprit. Most enterprise LLM…
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What Is AI Inference and Why It Matters for Apps

AI inference is the moment a trained model turns data into a decision. That single step powers every smart feature in a modern app. Newline's AI bootcamps include hands-on labs covering the inference setups you'll actually see in production. Here's the shortlist of the five modes the labs walk…
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NEW

Building AI Applications with RAG and Tool Use

If you want to learn RAG fast, these five platforms balance ready-made data connectors, decent docs, and reasonable setup effort. *Time estimates assume a small team (2‑3 engineers) following a typical bootcamp curriculum and include basic testing. Group RAG builds into three buckets and ask how…
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What Is AWQ in LLM Quantization and How It Works

AWQ stands for activation-aware weight quantization. It scales the most influential weight channels based on offline activation statistics, then quantizes everything else to ultra-low bit widths. By protecting a small fraction of salient weights, it keeps quantization error down without…
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Prompt Engineering Techniques for Better LLM Results

*Time estimates are approximate and reflect typical pacing for learners working through the course material. The simple techniques, like zero-shot and role prompting, take minutes to learn. The advanced ones, like self-consistency and RAG, take hours. They also assume you already understand how the…
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