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Unclaimed ProfileAspiring developers and AI enthusiasts looking to transition from basic prompt engineering to building fully autonomous systems will find exceptional value in Manas Roy's beginner-friendly guide to AI agents. This comprehensive course demystifies the complex world of autonomous AI, guiding learners step-by-step through the process of designing, developing, and deploying intelligent digital assistants. Students start with foundational concepts before quickly moving into practical implementations, such as configuring agent frameworks, setting up decision-making logic, and integrating robust memory systems. The curriculum places a strong emphasis on hands-on creation, teaching you how to equip your agents with custom tools and enable multi-agent collaboration where multiple virtual entities work together to solve complex business workflows. Beyond coding, the course addresses crucial production challenges, including error handling, performance monitoring, and deployment strategies. Whether you want to automate repetitive workplace tasks, streamline data processing pipelines, or build next-generation intelligent assistants, this course provides the framework-agnostic skills and practical confidence needed to turn static large language models into proactive, goal-oriented digital workers.
About the creator
Manas Roy | GenAI Instructor
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Manas Roy is a dedicated Generative AI instructor and technology educator who specializes in breaking down complex artificial intelligence frameworks into practical, accessible lessons for learners worldwide. With a course catalog spanning AI-driven finance, autonomous AI agents, prompt engineering, and visual asset generation using tools like Midjourney, DALL-E, and Adobe AI, Manas has built a reputation for delivering highly actionable, project-based training. His teaching methodology centers on bridging the gap between cutting-edge AI research and real-world execution. Rather than focusing solely on theoretical models, Manas guides his students through step-by-step builds, whether they are crafting custom GPT workflows, building autonomous…Show more
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Program Overview
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Learning format
Subcategory
Price
Price may change · updated within 1–2 weeks
Course language
What You'll Learn
- How to build autonomous AI agents from scratch that can perform tasks independently.
- Setting up and configuring agent frameworks and tooling for real-world applications.
- Implementing memory systems, tool usage, and decision-making logic in AI agents.
- Deploying AI agents to production environments and monitoring their performance.
- Real-world use cases including automation, data processing, and intelligent assistants.
- Building multi-agent systems that can collaborate and coordinate tasks.
- Best practices for prompt engineering, error handling, and agent reliability.
Best For
- Developers looking to move beyond basic LLM prompting into autonomous agent workflows
- Automation engineers aiming to build intelligent systems that handle multi-step business tasks
- Tech-savvy professionals who want to transition from static chatbots to goal-oriented digital assistants
- Students seeking a structured, project-based introduction to AI agent frameworks and multi-agent coordination
Not For
- Individuals without any prior experience in programming or basic Python scripting
- Research scientists looking for highly theoretical, academic, or mathematical deep-dives into LLM architecture
- Learners searching for a 'no-code' tool tutorial that does not require an understanding of logic and systems design
- Users looking for a course focused exclusively on passive text generation rather than active task execution
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