Tag: Maven

AI Software Development with opencode is a practical course for developers who want to use artificial intelligence in programming without full dependency on cloud services, maintaining control over the code, data, infrastructure, and development process.

Master web design principles and build a portfolio-ready landing page in Figma from start to finish.

Most practitioners don’t struggle with access to data. They struggle with knowing what matters — and AI made it worse, not better. Most AI research courses teach extraction: summarize quicker, automate the asking, replacing the human with the synthetic.

This practical course will help developers, team leads, and engineers move from the occasional use of AI tools to full-fledged AI-first development, speeding up the release of functionality and improving code quality. The foundation of the program is based on real work experience with Stanford, Y Combinator, and engineering teams at Amazon.

Practical AI Bootcamp that will guide you from the basics of working with LLM to creating full-fledged production-ready AI applications. Over 6 weeks, you will master RAG, agent frameworks, tools for monitoring and quality evaluation, and create your own AI assistant ready for real-world deployment.

In 2026, engineering value is shifting from task execution to orchestration and systems thinking. Anthropic’s research shows that being a software engineer increasingly means orchestrating agents that write code, evaluating their output, and ensuring the system solves the right problems—not just writing more code yourself. The gap between early adopters and everyone else is widening fast.

AI Problem Framing is to AI teams what System Design is to software engineers and Product Sense is to PMs. Whether you’re building, evaluating, or leading AI work, this is the foundational thinking skill that separates results from rework.

The End-to-End AI Engineering Bootcamp is an 8-week, cohort-based experience designed to turn technical professionals into full-stack AI engineers who can confidently design, build, and deploy production-grade AI systems.

Master AI Concepts with a Real LLM Implemented Entirely in a Spreadsheet. No Complex Math. Just Clarity.

Most AI projects are held back not because of technology, but because they fail compliance and safety checks. This system “from pilot to industrial deployment” provides you with the frameworks, language, and tools needed to transition from an AI idea to a safe and compliant implementation.

Make it code like you do. Turn generic AI assistants into coding partners that actually get your style and have the right context.

Learn to make decisions tailored to business constraints, understand when & how to apply AI effectively & build a multi-agent application

Analytics Engineering is the foundation of Data Science and artificial intelligence. This approach represents a dynamic blend of data engineering and analytics, acting as a bridge between these two fields. Analytics engineers are responsible for a significant portion of the data lifecycle: from loading data sources and building data warehouses with corresponding pipelines to integration with business intelligence tools.

Discover AI capabilities to design and develop products and user experiences – without a single line of code.

In this course, you will master a step-by-step process: from asking the right questions to creating powerful data-driven stories that will help you achieve your professional and personal goals.

Learn proven methods for quickly improving AI applications. Build AI systems that outperform competitors, regardless of the specific use case.

Become an AI Engineer in the world’s leading community for people who want to build, ship, and share production LLM applications 🏗️🚢🚀.

Master the what, why, and how of Generative AI by building Enterprise-Grade Agents that go beyond the basics and actually move the needle

Most RAG implementations get stuck in prototype purgatory. They work well for simple cases but fail on complex queries—leading to frustrated users, lost trust, and wasted engineering time.