Johns Hopkins University is offering a focused, practical Certificate Program in Agentic AI designed to teach how to design and deploy autonomous AI agents. Delivered fully online over 16 weeks, the program emphasizes hands‑on learning with real projects that put theory into practice.
What you’ll learn: the curriculum blends core engineering skills (Python, Google Colab, VS Code) with modern agentic tooling and patterns. The program shows how to integrate Large Language Models and retrieval systems using tools such as OpenAI LLMs, LangChain and LangGraph, vector databases (Chroma/Pinecone), RAG (retrieval‑augmented generation), DSPy and OpenAI Autogen. Students build practical projects — for example, a Smart Data Processing Agent to automate employee expense processing — that demonstrate how agentic systems can reason, plan and act autonomously.
Faculty and mentorship: the course is designed and taught by Johns Hopkins faculty together with industry practitioners. The program listing names instructors including Dr. Shelby Wilson (Senior Data Scientist at the Johns Hopkins University Applied Physics Laboratory) and highlights industry mentors from companies such as Apple, BlackRock, Workday, Newmark and Capital One.
Outcomes and logistics: upon completion participants receive a Johns Hopkins Certificate of Completion and 11 Continuing Education Units. The program is marketed for professionals who want to design systems that autonomously perform tasks, make decisions and adapt to changing environments. The published fee is $3,000; the site notes the fee is generally non‑refundable and that rolling admissions apply, so candidates are advised to apply early.
Why it matters: as organizations look to move beyond single‑turn LLM prompts to multi‑step, action‑oriented workflows, the program promises practical, tool‑centric experience — not just concepts. For learners seeking a structured, university‑backed way to build production‑oriented agentic AI skills, the Johns Hopkins certificate presents a concrete, hands‑on option.

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