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GenAI for Data Analytics

4.50
2,080 students
8h 49m
Updated Feb 2026

What you'll learn

Design and implement comprehensive data pipelines for GenAI applications.
Develop and deploy autonomous AI agents and multi-agent systems.
Analyze prompt engineering and chain management for LLMs.
Build production-ready GenAI applications with monitoring and safety systems.

Course Description

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.

By the end of this course, you will be able to:

  • Design and implement comprehensive data pipelines for GenAI applications.

  • Build and deploy autonomous AI agents that can solve complex tasks.

  • Master prompt engineering techniques for optimal LLM performance.

  • Implement RAG (Retrieval-Augmented Generation) systems for knowledge-intensive applications.

  • Fine-tune foundation models to excel at specialized tasks.

  • Deploy production-ready GenAI systems with proper monitoring and safety guardrails.

  • Develop multi-agent systems that collaborate to solve complex problems.

Don't just be a consumer of AI technology – become a creator who can engineer the next generation of intelligent systems. Join us and transform your theoretical knowledge into practical engineering skills that are in high demand across industries. Enroll now and start building the future of AI!

Requirements

  • Learners should have experience with Python programming and a basic understanding of machine learning concepts. Familiarity with APIs, cloud platforms, and command-line tools will help participants easily follow along with the practical exercises and implementation labs.

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Course Details

  • Level Intermediate
  • Lectures 133
  • Duration 8h 49m