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Unclaimed ProfileThe Agentic AI Masterclass 2026: Build Autonomous AI Agents course, designed by Geeta Patwal, offers a forward-looking roadmap into the world of agentic workflows and autonomous digital assistants. As artificial intelligence transitions from passive conversational tools to proactive, goal-oriented agents, mastering this technology is crucial for modern tech professionals, developers, and productivity enthusiasts. This masterclass demystifies how self-directing AI systems function, planning and executing multi-step tasks without human intervention. Throughout the curriculum, learners explore the mechanics of agentic reasoning, tool calling, and workflow design. The course bridges theory and practice, providing step-by-step guidance on constructing real-world agents using powerful no-code tools and optional Python integrations. Students will learn to architect agents capable of conducting deep market research, drafting context-aware emails, automating content pipelines, and executing complex workflows. By understanding the intersection of prompt engineering, large language models (LLMs), and API integrations, students gain the confidence to implement autonomous systems that drastically reduce manual operational overhead. This program is ideal for anyone looking to stay ahead in the rapidly evolving AI landscape, turning theoretical understanding into deployed, self-sufficient AI solutions.
About the creator
Geeta Patwal
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Geeta Patwal is a dedicated technology educator and systems specialist committed to demystifying the rapidly evolving landscape of artificial intelligence. With a strong focus on practical implementation, Geeta helps developers, software engineers, and tech enthusiasts transition from understanding theoretical machine learning concepts to building fully functional, autonomous AI systems. As the instructor for the Agentic AI Masterclass 2026, Geeta focuses on the cutting-edge shift toward multi-agent orchestration, self-correcting workflows, and practical tool integration. Her teaching methodology prioritizes hands-on project creation, encouraging learners to construct real-world agents that can plan, execute, and adapt independently. By breaking down complex paradigms—such as chain-of-thought…Show more
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Program Overview
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Learning format
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Price
Price may change · updated within 1–2 weeks
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What You'll Learn
- Analyze the core architecture of agentic AI systems, focusing on how autonomous agents leverage reasoning, memory, and planning to execute complex, multi-step operations.
- Design and deploy practical, autonomous AI agents capable of orchestrating web research, automated content curation, and context-sensitive email draft generation.
- Implement advanced prompt engineering and orchestration strategies to define precise agent roles, constraints, and dynamic routing workflows.
- Leverage visual, no-code automation platforms alongside optional Python scripts to build, test, and debug custom AI tools that integrate seamlessly with external APIs.
- Configure tool-calling behaviors and external resource access, enabling AI agents to interact dynamically with databases, file systems, and web services.
- Optimize agent-based workflows to eliminate repetitive manual processes, maximize operational throughput, and establish robust error-handling mechanisms in autonomous tasks.
Best For
- Software developers and engineers looking to transition from basic LLM integration to autonomous workflow orchestration.
- Productivity enthusiasts and business professionals who want to automate complex, multi-step digital tasks without constant human oversight.
- Tech consultants aiming to build and deploy custom agentic solutions for client operations and research pipelines.
- Data analysts seeking to integrate AI agents into their existing data extraction and reporting workflows.
Not For
- Absolute beginners with no exposure to AI concepts, LLMs, or foundational prompt engineering.
- Professionals looking for a deep-dive, code-heavy software engineering course focused solely on backend machine learning model training.
- Individuals seeking theoretical research papers on the future of AGI rather than actionable, project-based agent building skills.
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