Multi Agents Series

WSQ Manage AI Agents with Paperclip is a practical, hands-on course that equips participants with the knowledge and skills to build, deploy, and manage intelligent AI agents for business automation. Participants will learn the fundamentals of Agentic AI, understand how AI agents differ from traditional chatbots, and discover how autonomous agents can reason, use tools, access knowledge, and collaborate to complete co....

This WSQ Develop Multi-Agent AI Applications with AutoGen course equips learners with hands-on skills to build intelligent AI systems using cutting-edge tools like AutoGen and CrewAI. Participants will learn how to create AI agents using Autogen AgentChat, understand the architecture and capabilities of large language models (LLMs), and critically evaluate their strengths and limitations in real-world applications. ....

This comprehensive course is designed to equip participants with the skills to leverage Neo4j Graph Data Science (GDS) and Large Language Model (LLM) technologies to enhance data-mining applications and resolve complex data challenges. Beginning with an introduction to Neo4j GDS, learners will gain an understanding of how GDS operates, including its Graph Catalog and Cypher Projections, setting a solid foundation for....

This WSQ-certified course equips you with the skills to design, build, and deploy multi-agent AI systems using modern vibe coding techniques. You will explore the foundations of AI agents, including agent skills as modular transferable capabilities, agent memory systems, and Model Context Protocol (MCP) fundamentals. Through hands-on projects, you will learn structured vibe coding workflows, context engineering for r....

This WSQ Develop AI Agents with OpenAI Agent Development Kit course equips learners with practical skills to build, evaluate, and fine-tune AI agents using OpenAI's latest tools. Participants will gain deep insights into large language models (LLMs), understand their applications, and learn to work with word embeddings and vector databases to implement retrieval-augmented generation (RAG). The course also covers asse....

Master the development of advanced Artificial Intelligence (AI) solutions by leveraging the power of Google Gemini's Large Language Models (LLMs). This course begins with a comprehensive overview of LLMs, their industrial use cases, and introduces you to Google Gemini. Explore multimodal prompting through Google AI Studio and Vertex AI, gaining practical experience with workflows that integrate Gemini's capabilities.....

This comprehensive course equips participants with the expertise to evaluate, build, and optimize Large Language Models (LLM) powered chatbots, aimed at transforming customer service operations. Participants will delve into the fundamentals of Generative AI (GAI) and LLM, understand the practical applications of LLM-powered chatbots, and explore various no-code chatbot builders to compare their strengths and limitati....

Build a Human–AI Workforce with Autonomous AI Agents equips participants with practical skills to develop, deploy, and manage autonomous AI agents that collaborate with people and other agents in a digital workforce.Participants will begin by building LLM-powered applications with Hermes Agent. They will learn how to configure autonomous agents, connect tools and APIs, define agent skills, and design intelligent wo....