Design, evaluate, and deploy next-gen Claude Mythos agents for coding, reasoning, and secure enterprise workflows
Sub Category
- Data Science
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Objectives
- Build agentic AI systems that go beyond prompting by combining planning, execution, and evaluation workflows
- Design and implement multi-agent architectures using the Planner → Executor → Critic pattern
- Apply dual-mode reasoning and create structured outputs such as JSON plans and execution graphs
- Develop AI-powered solutions for code review, debugging, refactoring, and system design
- Create security-aware AI systems that detect vulnerabilities and generate risk reports with remediation steps
- Integrate memory systems (FAISS/Chroma patterns) to enable context retention and long-running workflows
- Implement guardrails, policy engines, and human-in-the-loop approval workflows for enterprise readiness
- Use LLM-as-a-judge evaluation techniques to measure quality, reliability, and performance of AI outputs
- Build systems with tool usage and API integration for real-world automation
- Design observability pipelines with logging, tracing, and cost monitoring for AI systems
- Design observability pipelines with logging, tracing, and cost monitoring for AI systems
- Deliver a complete production-grade frontier AI system as a portfolio-ready capstone project
Pre Requisites
- Basic understanding of Python programming (functions, APIs, JSON handling)
- Familiarity with AI/LLM concepts such as prompts, tokens, and model behavior
- Experience using tools like OpenAI API or similar LLM providers (helpful but not mandatory)
- A development environment set up with Python 3.10+, terminal/command line, and a code editor (e.g., Visual Studio Code)
- Ability to read and understand basic code workflows (no advanced software engineering required)
- Curiosity to learn agentic AI systems, multi-agent workflows, and real-world AI applications
- Willingness to build hands-on projects and experiment with prompts, agents, and system design
- Internet connection and ability to install Python packages and run scripts locally
- No prior experience with multi-agent systems is required—this course builds everything step by step from foundational concepts to advanced systems
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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Coupon Code(s)