GenAI Data and Analytics Academy
In this comprehensive journey, you'll master not just the theory, but the actual engineering practices that power today's most advanced AI systems. From crafting robust data pipelines that feed your models, to building autonomous agents that can reason and act on their own, to deploying systems that scale reliably in production – we've got you covered.
Intermediate
Finance
29 hours 30 minutes
Overview
Ever wondered how ChatGPT-like systems are built and deployed in the real world? Ready to move beyond basic prompts to creating your own AI agents? Welcome to "Generative AI Engineering" – your complete guide to building production-ready AI systems that actually work.
In this comprehensive journey, you'll master not just the theory, but the actual engineering practices that power today's most advanced AI systems. From crafting robust data pipelines that feed your models, to building autonomous agents that can reason and act on their own, to deploying systems that scale reliably in production – we've got you covered.
Whether you're looking to build the next groundbreaking AI application or enhance existing systems with state-of-the-art generative capabilities, this course provides the practical, hands-on experience you need to make it happen.
Skills you'll gain
Data AnalysisData AnalyticsGenAIGenAI Academy
What you'll learn
- Design and implement comprehensive data pipelines for GenAI applications
- Develop and deploy autonomous AI agents and multi-agent systems
- Master prompt engineering and chain management for LLMs
- Build production-ready GenAI applications with monitoring and safety systems
Who Should Attend
- Software Engineers transitioning to AI
- Data Scientists expanding into GenAI
- ML Engineers focusing on LLMs
- DevOps Engineers handling AI deployments
Program
Explore the comprehensive, hands-on program designed to build your expertise in everything from business functions.
*Where courses have been offered multiple times, the “# Students” includes all students who have enrolled. The “%Recommended” shown is also based on this data.
