Generative AI Automation Tools and Applications

Übersicht

This course offers a practical pathway to understand how Generative AI can transform enterprise automation, streamlining workflows, enhancing decision-making, and reducing manual effort. You’ll learn to design, build, and scale AI-driven automation solutions using low-code tools, open-source frameworks, and advanced agent orchestration techniques.

Through hands-on exercises, you’ll gain the skills to connect APIs, chain AI agents, test and debug workflows, and deploy real-world automations for business processes such as customer support, sales, and decision support. By the end of this course, you will be able to:

- Explain the principles of Generative AI automation and its role in enterprise workflows - Use tools like LangChain, Flowise, n8n, Make, Zapier, Open AI, and Hugging Face for automation tasks - Build low-code workflows integrating AI models, APIs, and event triggers - Design error-tolerant, human-in-the-loop, and multi-agent automation patterns - Scale and monitor automation solutions in cloud environments with proper security and compliance - Apply best practices and understand future trends in Generative AI-driven business automation This course is ideal for automation specialists, solution architects, developers, and business professionals looking to leverage Generative AI to create scalable, intelligent, and efficient enterprise workflows.

Join us to learn how Generative AI is shaping the future of enterprise automation—and how you can put it to work for your organization.

Lehrplan

• Generative AI Automation Tools
This module introduces the foundations of Generative AI automation, covering essential concepts, frameworks, and platforms. Learners will explore tools such as LangChain, Flowise, Hugging Face, OpenAI APIs, and Zapier/Make, CrewAI, LangGraph gaining hands-on experience in building simple low-code AI workflows and connecting APIs for real-world automation tasks.
• Automation Patterns
This module focuses on core automation patterns used to design intelligent workflows. It covers decision-making flows, human-in-the-loop processes, error handling, event-based task triggers, and multi-agent orchestration. Learners will build and test multi-step automation pipelines, learning how to improve reliability and efficiency in AI-driven workflows.
• Scaling and Applying GenAI Automation
This module teaches how to scale AI-powered workflows using cloud platforms like Google Colab and Hugging Face Spaces. It explores real-world applications in customer support, sales, and marketing, emphasizing security, compliance, and workflow optimization. Learners will complete a hands-on, end-to-end project to apply all concepts and tools in a practical, business-focused automation solution.
• Course Wrap-Up and Assessment

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Unterrichtet von

Edureka

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Fachgebiete

Computer Science