Agentic AI—designing AI agents that act autonomously or in multi‑agent teams—is surging in importance. Below are the ten best certification paths worldwide, ranked with ADaSci’s new program at the top. Each entry includes program details, pros, and cons.

Offered by the ADaSci, this certification begins with a 30‑hour, self‑paced online course that blends video lectures, readings, case studies, and hands‑on exercises. Once you’ve completed the coursework, you’ll sit a 60‑question, one‑hour proctored exam, which you can schedule and take online at any time of year.

The curriculum dives into the foundations of agentic AI architecture, introduces you to leading tools and frameworks such as LangChain and AutoGen, and explores deployment strategies for both cloud and edge environments. You’ll also study governance, ethics, and security concerns for autonomous agents before examining real‑world case studies across industries to see these concepts in action.

This program is designed for AI engineers, system architects, business analysts, and product managers who already have basic Python and large‑language‑model knowledge and want to build and manage scalable agentic systems. At USD 249 (covering both the course and exam), it’s very affordable compared to similar offerings. Upon passing, you earn a globally recognized ADaSci credential that carries lifetime validity, with no renewal fees required.

Although the curriculum is developed by ADaSci’s expert panel to reflect current industry best practices, the self‑paced format means there are no named instructors or scheduled live sessions for individuals—corporate teams can arrange in‑house training if they need guided support. The flexible structure and hands‑on exercises ensure you gain both practical skills and formal validation, but access to the course materials ends after your exam attempt, and you’ll need strong self‑discipline, with limited opportunities for networking.

Access certification:
https://adasci.org/certified-agentic-ai-system-architect-program/

2. IBM RAG & Agentic AI Professional Certificate

Provider: IBM (via Coursera)
Format & Duration: Eight self‑paced online courses, ~2 months at 3 hrs/week
Curriculum Focus:

  • Generative AI pipelines (prompt chaining, function calling)
  • Retrieval‑Augmented Generation (RAG)
  • Multimodal AI integration
  • Designing and orchestrating autonomous multi‑agent systems using LangChain, LangGraph, CrewAI, BeeAI, etc.
    Target Audience: Advanced AI engineers or data scientists with Python experience
    Cost: ~USD 49/month (Coursera subscription)
    Credential: IBM Professional Certificate

Pros:

  • Comprehensive, up‑to‑date content
  • Hands‑on labs and capstone projects
  • Industry recognition from IBM

Cons:

  • Requires significant time commitment
  • Assumes prior AI/ML and Python knowledge

Access certification:
https://www.coursera.org/professional-certificates/ibm-rag-and-agentic-ai

3. Certificate Program in Agentic AI

Provider: Johns Hopkins University (in partnership with Great Learning)
Format & Duration: 16 weeks online (part‑time), live sessions + recorded lectures
Curriculum Focus:

  • Classical agent architectures (BDI models)
  • LLM‑based agents and multi‑agent systems
  • Reinforcement learning for agent behavior
  • Responsible AI, safety, and ethics
    Target Audience: Mid‑ to senior‑level professionals with some AI background
    Cost: USD 3,000
    Credential: Johns Hopkins University Certificate

Pros:

  • Rigorous academic curriculum
  • Strong theoretical foundations and practical projects
  • Prestigious university credential

Cons:

  • High tuition
  • Structured schedule may be hard alongside full‑time work

Access certification:
https://online.lifelonglearning.jhu.edu/jhu-certificate-program-agentic-ai

4. AI Agents Course

Provider: Hugging Face (free, self‑paced)
Format & Duration: ~5–6 weeks recommended at 3–4 hrs/week
Curriculum Focus:

  • Agent fundamentals (Tools → Thoughts → Actions → Observations)
  • smolagents, LlamaIndex, LangGraph frameworks
  • Agentic RAG use cases
  • Final project on deploying your own AI agent
    Target Audience: Beginners to intermediate developers (basic Python & LLM familiarity)
    Cost: Free
    Credential: Certificate of Completion from Hugging Face

Pros:

  • Completely free and community‑driven
  • Covers multiple open‑source frameworks
  • Interactive notebooks and Discord support

Cons:

  • No formal university or corporate backing
  • Self‑directed learning requires discipline

Access certification:
https://huggingface.co/learn/agents-course

5. AI Agent+ Certification

Provider: Dallas College & Web3 Certification Board (W3CB)
Format & Duration: 20 hours total (10 hrs live + 10 hrs self‑study) + proctored exam
Curriculum Focus:

  • LLM automation workflows (Zapier/Make integration, RAG)
  • Agent orchestration (LangGraph, CAMEL)
  • Vector memory, reasoning loops, multi‑agent coordination
  • Governance: security, ethics, human‑in‑the‑loop
    Target Audience: Practitioners with foundational AI expertise
    Cost: USD 1,495
    Credential: AI Agent+ Certification (on‑chain badge)

Pros:

  • Enterprise‑focused with real‑world use cases
  • Live instruction plus capstone projects
  • Verifiable, on‑chain credential

Cons:

  • Relatively expensive for a short program
  • Cohort schedules may not suit everyone

Access certification:
https://web3.dallascollege.edu/ai-agent-certification/

6. Agentic AI Training Course

Provider: Edureka
Format & Duration: 5 weeks live weekend classes + bonus self‑paced module
Curriculum Focus:

  • LangChain, LangGraph, AutoGen, CrewAI hands‑on labs
  • Agent observability (LangFuse, LangSmith)
  • No‑code AI agent development (LangFlow, Relevance AI)
  • Cloud deployment on AWS Bedrock, Azure OpenAI, GCP Vertex AI
    Target Audience: Intermediate practitioners (Python & ML basics recommended)
    Cost: ₹24,999 (≈ USD 300)
    Credential: Edureka Agentic AI Certification

Pros:

  • Affordable, mentor‑led live sessions
  • Broad coverage of tools and cloud platforms
  • Weekend schedule for working professionals

Cons:

  • Intensive pace on weekends
  • Training‑provider credential, less academic recognition

Access certification:
https://www.edureka.co/agentic-ai-training-course

7. AI Agentic Design Patterns with AutoGen

Provider: DeepLearning.AI
Format & Duration: ~1.5 hrs self‑paced short course
Curriculum Focus:

  • Agentic design patterns (Reflection, Tool Use, Planning, Collaboration)
  • Hands‑on coding with the AutoGen framework (Microsoft)
  • Projects: multi‑agent chats, nested‑chat workflows, tool‑enabled chess game
    Target Audience: Developers with basic Python & LLM API experience
    Cost: Free (with DL.AI account)
    Credential: Certificate of Completion from DeepLearning.AI

Pros:

  • Taught by AutoGen creators (Microsoft Research)
  • Very up‑to‑date, research‑driven content
  • Quick deep‑dive into advanced patterns

Cons:

  • Focused only on AutoGen
  • Limited hands‑on projects

Access certification:
https://www.deeplearning.ai/short-courses/ai-agentic-design-patterns-with-autogen/

8. AI Agents in LangGraph

Provider: DeepLearning.AI
Format & Duration: ~1.5 hrs self‑paced short course
Curriculum Focus:

  • Building and debugging agents with Python
  • Rebuilding agents using LangGraph flow‑based components
  • Agentic search and state persistence
  • Human‑in‑the‑loop integration
    Target Audience: Intermediate developers familiar with LangChain basics
    Cost: Free
    Credential: Certificate of Completion from DeepLearning.AI

Pros:

  • Co‑created by LangChain founder and industry experts
  • Teaches robust, controllable agent patterns
  • Quick completion time

Cons:

  • Assumes LangChain experience
  • Short coverage of topics

Access certification:
https://www.deeplearning.ai/short-courses/ai-agents-in-langgraph/

9. Multi‑AI Agent Systems with CrewAI

Provider: DeepLearning.AI
Format & Duration: ~2.5 hrs self‑paced short course
Curriculum Focus:

  • Defining specialized agent roles (role‑playing)
  • Memory types (short‑term, long‑term, shared)
  • Tool integration and guardrails
  • Business process automation examples (resume tailoring, event planning)
    Target Audience: Beginners with some Python/prompting experience
    Cost: Free
    Credential: Certificate of Completion from DeepLearning.AI

Pros:

  • Highly practical business use cases
  • Focus on reliability and error handling
  • Fast ROI in under 3 hrs

Cons:

  • CrewAI‑specific implementation
  • Introductory level content

Access certification:
https://www.deeplearning.ai/short-courses/multi-ai-agent-systems-with-crewai/

10. Deploy Multi‑Agent Systems with ADK & Agent Engine

Offered by Google Cloud Skills Boost (Qwiklabs), this program delivers approximately 6 hours of hands‑on labs in a live Google Cloud environment. You’ll learn to build AI agents with the Google Agent Development Kit (ADK), equip those agents with tools and parent‑child workflows, and deploy them to the Vertex AI Agent Engine for managed scaling. Along the way, you’ll practice cloud‑native agent orchestration in real‑world scenarios.

This track is ideal for ML engineers and Generative AI engineers who are already comfortable with GCP. Access is via a subscription or pay‑per‑lab model—notes that many learners use free credits. Upon completing all labs, you earn an official Google Cloud completion badge, a digital credential you can share on LinkedIn or your resume.

The key benefits include gaining real‑world cloud deployment experience with official Google Cloud tooling and earning a shareable digital badge backed by Google. On the flip side, the curriculum is platform‑locked to GCP, and its lab‑first approach means it lacks deep theoretical coverage, focusing more on practical skills than on underlying concepts.

Access it here >

Representing an organization and looking to upskill your team in agentic AI? Drop us a line at info@aimmediahouse.com.