Agent Academy

Agent Academy is designed for learners at all levels, from beginners exploring AI agents for the first time to developers building advanced multi-agent systems and workflows. With courses ranging from introductory foundations to advanced development topics, the academy is built to support learners at every stage of their agentic AI journey.

Yes! Every learning track in Agent Academy ends with a final exam. Pass it and you will receive an official Cognizant AI Lab certification badge that you can download and share. The badge is a recognized credential that demonstrates your knowledge of agentic AI, whether you are an engineer, a leader, or someone exploring this space for the first time. There is no time limit on the exam and you can retake it as many times as you need. Your certification is yours to keep.

Not at all! Agent Academy includes foundational courses that introduce the core concepts behind AI agents and multi-agent systems before moving into more advanced topics and hands-on development.

Agent Academy covers the full lifecycle of agentic systems, from foundational concepts to real-world implementation. Topics include AI agents and multi-agent systems, agentic RAG, responsible AI, agent design principles, vibe-coding, observability, agent testing, debugging, integrations, and building scalable agentic workflows with Neuro San.

Agent Academy includes four certification curses designed to guide learners from foundational concepts to advanced agent development.

1. Agent Foundations introduces the core concepts behind AI agents and multi-agent systems.

2. Agent Design focuses on designing reliable, secure, and scalable agentic workflows.

3. Quickstart: Neuro San provides hands-on introduction to building with the open-source agentic framework.

4. Production-Ready Agentic Systems explores more advanced topics such as integrations, testing, observability, debugging, and production-ready agent systems using Neuro San.

Yes. The learning tracks are designed to build progressively, starting with foundational concepts before moving into agent design, hands-on development, and advanced workflows with Neuro San. However, learners can also jump directly into the track that best matches their experience level or areas of interest.

Agent Academy combines foundational education with practical, real-world agent development. Courses are curated by leading AI researchers, engineers, and developers working on modern multi-agent systems and enterprise AI infrastructure, giving learners direct exposure to the architectures, workflows, and development patterns shaping the next generation of agentic AI.

The academy is designed for learners at every stage, from those exploring AI agents for the first time to developers building advanced multi-agent networks. Beyond teaching how to build agent systems, Agent Academy also focuses on the topics required to make those systems reliable and production-ready, including observability, testing, safety, security, orchestration, and responsible AI.

Rather than focusing only on isolated demos or theoretical concepts, Agent Academy emphasizes practical implementation and real-world system design. Learners gain hands-on experience building scalable agentic workflows with Neuro San while developing the skills needed to design systems that can operate effectively in real environments.

Neuro San is the AI Lab's open source, data-driven library designed to simplify and accelerate the development of multi-agent systems. It allows users – from machine learning engineers to business domain experts – to quickly build sophisticated multi-agent applications without extensive coding, using declarative configuration files (in HOCON format). Key features include:

• Adaptive Communication (AAOSA Protocol): Agents autonomously determine how to delegate tasks, making interactions fluid and dynamic with decentralized decision-making.
• Sly-Data: Sly Data facilitates safe handling and transfer of sensitive data between agents without exposing it directly to any language models.
• Rapid vibe-coding: Includes a meta-agent called the Agent Network Designer that creates other agent networks with just a use case description. 
• Flexible Tool Integration: Integrate custom Python-based "coded tools," APIs, databases, and even external agent ecosystems (Agentforce, Agentspace, CrewAI, MCP, A2A agents, LangChain tools and more) seamlessly into your agent workflows.
• Robust Traceability: Detailed logging, tracing, and session-level metrics enhance transparency, debugging, and operational monitoring.

Not at all! Agent Academy includes introductory lessons, quickstart modules, tutorials, and example projects designed to help learners understand the core concepts of agents and get started with Neuro San from the ground up. For more experienced developers, the academy also includes advanced modules covering topics such as MCP integrations, observability, debugging, testing frameworks, and scalable multi-agent workflows.

Yes! After completing a learning track course, you will receive an official Cognizant AI Lab certificate that you can upload directly to your LinkedIn and socials. 

Yes! The first learning track, Agent Foundations, is currently available. However, more tracks and modules are coming soon. Agent Academy will continue expanding with new advanced learning tracks and hands-on courses focused on building real-world agent systems with Neuro San. While the foundational tracks focus on core concepts and agent design principles, upcoming content will go deeper into how to actually design, build, and deploy reliable, safe, and scalable agentic systems using the open-source framework.

This includes beginner-friendly quickstarts for building your first agent networks, as well as more advanced topics such as MCP integrations, observability, testing frameworks, debugging, memory and data management, autonomous workflows, and production-ready multi-agent system design.