Tech Events & Workshops

A practical two-hour session on the principles behind document question-answering systems, with Rust as the implementation context. The session focuses on how applications can answer questions from a known set of documents instead of relying only on what a language model already knows. We will cover the core workflow: loading documents, preparing them for search, finding relevant passages, passing useful context to a model, and producing answers that stay connected to the source material. The goal is to teach the engineering ideas behind RAG systems without turning the session into a product demo or an abstract AI lecture. The emphasis is on system boundaries, retrieval quality, answer grounding, error handling, and the practical decisions developers need to make when building document-aware applications. Audience: entry-level and intermediate developers who want a practical session on document search, retrieval, grounded generation, and Rust application design. Outcomes: * Understand how document-based question answering systems work * Explain the purpose of chunking, embeddings, retrieval, and context assembly * Design a simple retrieve-first, answer-second workflow * Use Rust to organize the main parts of a small RAG application * Recognize common causes of poor or unsupported answers * Apply basic techniques for improving retrieval and answer quality * Think about how to evaluate whether the system is actually useful Format: two hours with a short framing walkthrough, a concrete example, discussion of tradeoffs, and a closing checklist for practice.

A practical two-hour session on building reliable data pipelines in Rust, starting from messy input files and ending with clean data that can be stored, queried, and visualized in a web application. The session combines Rust, Polars, command-line data workflows, and SQLx to show how a developer can take CSV or Parquet files, validate and transform the data, handle errors clearly, persist clean records into a database, and prepare the results for charts, dashboards, or reporting screens. Rust is used as the implementation context, but the main lesson stays focused on software engineering fundamentals: data contracts, repeatable workflows, visible progress, reliable error handling, database migrations, compile-time query checks, and operational clarity. Audience: entry-level and intermediate developers who want a practical engineering session on turning raw files into clean, queryable, visualizable data. Outcomes: * Build a Rust command-line workflow that accepts input files and produces structured outputs * Clean and validate CSV or Parquet data before storing it * Use Polars for filtering, selecting, joining, grouping, and lazy execution * Store clean records in a database with SQLx * Use migrations and compile-time checks to make database access safer * Prepare stored data for visualization in a web application Format: two hours with a short framing walkthrough, a concrete end-to-end example, discussion of tradeoffs, and a closing checklist for practice.