Tech Events & Workshops
Discover and join virtual tech events, workshops, and meetups from the Ubuntu community worldwide. Connect with developers, engineers, and tech enthusiasts.
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Rust Data Pipelines: From Files to Clean Databases and Web Dashboards
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.
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Rust Data Pipelines: From Files to Clean Databases and Web Dashboards
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.
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De consommateur à créateur : prenez une longueur d’avance avec l’Intelligence Artificielle !
What if AI became your best tool for professional growth, creating faster, and seizing new opportunities? Join this exceptional free webinar organized by FasoCode-X and discover how to transform the way you work through artificial intelligence, data, and the cloud. Whether you are a student, entrepreneur, professional, or digital enthusiast, this event is a unique opportunity to understand the challenges and opportunities of AI in today's world.
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Rust Data Processing with Polars: CSV, Parquet, Joins, and Lazy Queries

Rust Data Processing with Polars: CSV, Parquet, Joins, and Lazy Queries

The Polylith Mindset: Build Faster Across Multiple Projects

The Polylith Mindset: Build Faster Across Multiple Projects

Building a voice agent for your business

Building a voice agent for your business

Save Tokens and Build with Data-Driven Clarity using Clojure(Script) -- Part 2

Save Tokens and Build with Data-Driven Clarity using Clojure(Script) -- Part 2
