Scale AI and Agentic AI to Drive Innovation
Certificate Program in AI and Agentic AI Engineering
Speak with our expert
+16673270271
Learn more about the course
Get details on syllabus, projects, tools, and more
Certificate Program in AI and Agentic AI Engineering
Program Outcomes
Accelerate Innovation with AI
Learn end-to-end AI engineering for real-world impact.
-
Design and deploy cloud-based AI/ML systems using end-to-end MLOps pipelines.
-
Operationalize and scale Generative AI and Agentic AI solutions with LLMOps on cloud platforms.
-
Monitor and evaluate Agentic AI systems using performance metrics, observability, and security practices.
-
Apply responsible AI, governance, and data security principles across AI system design and deployment.
Johns Hopkins University
-
#9 National University Rankings
U.S. News & World Report, 2027
-
#2 Computer Information Technology
U.S. News & World Report, 2027
-
#11 Most Innovative Schools
US News and World Report, 2027
-
#17 Best Global University
U.S. News & World Report, 2027
-
#1 Biomedical Engineering Program
US News and World Report, 2027
Key Program Highlights
Why choose this program?
-
Faculty & Expert-led Learning
Delivered online through recorded lectures, weekly live sessions with global industry experts, and monthly masterclasses by Johns Hopkins University faculty.
-
Hands-on Learning Experience
Build industry-ready skills to design, deploy, and operate AI systems in production using Great Learning cloud labs, hands-on projects, and real-world case studies.
-
Learning Support
Get personalized support from a dedicated Program Manager, academic mentors, peer communities, and AI-assisted learning support through Great Learning discussion forums and groups.
-
Build a Compelling ePortfolio
Create an industry-ready portfolio showcasing your expertise in AI tools, frameworks, and real-world applications.
-
Earn Recognized Credentials
On successful completion, earn a globally recognized Certificate of Completion and 10 CEUs from Johns Hopkins University.
-
Live Mentorship and Masterclasses
The program includes live mentorship by industry experts and live faculty-led masterclasses through a unique learning model that keeps learners on track with career goals.
Skills you will learn
AI/ML Fundamentals
Prompt Engineering
Large Language Models (LLMs)
Generative AI
Agentic AI Systems
Retrieval-Augmented Generation (RAG)
Data Management
Model Training
MLOps
LLMOps
CI/CD Pipelines
Workflow Orchestration
Multi-Agent Systems
AI Monitoring
Model Evaluation
Performance Metrics
Responsible AI Practices.
AI/ML Fundamentals
Prompt Engineering
Large Language Models (LLMs)
Generative AI
Agentic AI Systems
Retrieval-Augmented Generation (RAG)
Data Management
Model Training
MLOps
LLMOps
CI/CD Pipelines
Workflow Orchestration
Multi-Agent Systems
AI Monitoring
Model Evaluation
Performance Metrics
Responsible AI Practices.
view more
- Overview
- Curriculum
- Projects
- Tools
- Faculty
- Mentors
- Career Support
- Fees
This program is ideal for
Individuals looking to explore how Generative AI can solve real-world business problems
-
AI/ML/DL Practitioners
Who have built models or POCs in Python and want to learn how to operationalize them at scale using MLOps, LLMOps, and AIOps best practices.
-
GenAI and Agentic AI Builders
Who have experimented with LLMs, OpenAI APIs, or agentic workflows and want to advance to secure, monitored, and reliable production deployments.
-
Data and Analytics Professionals
Who familiar with modeling and data pipelines who want to learn about the end-to-end AI lifecycle, including deployment, monitoring, and automation.
-
Technology Professionals, Architects and Leaders
Who are overseeing AI initiatives who want a structured framework to develop and scale AI and Agentic AI systems in real-world environments.
What will you learn in the program?
The curriculum is designed by faculty at Johns Hopkins University. It is taught by a best-in-class professor and practicing AI professionals. The program covers data management, model training and deployment, MLOps, monitoring, and LLMOps for production-grade Generative and Agentic AI applications.
-
Masterclasses
by JHU Faculty
-
20+
tools & technologies
-
2
hands-on projects
Pre-Work
This module covers foundational cloud concepts, introduces the cloud ecosystem, guides learners in setting up cloud environments, and provides an overview of real-world AI applications on the cloud. • Introduction to Cloud Concepts • Understanding Cloud Ecosystem • Real-World Use Cases for AI on Cloud
Module 1: AI Ops Foundations
This module lays the groundwork for AI operations by covering the fundamentals of Artificial Intelligence and Machine Learning. It introduces key concepts, drivers, and frameworks for AIOps, with a deep dive into operationalizing data for AI and ML model training and evaluation cycle Week 01: Introduction to AI Ops and AI Engineering Week 02: Operationalizing Data for AI Week 03: Model Training and Evaluation
Module 2: Production-Grade Deployment With MLOps
This module focuses on the practical implementation of MLOps, covering the architecture and components of MLOps pipelines, including CI/CD principles and deployment strategies. Key topics include model monitoring, degradation, drift detection, and ensuring version control and reproducibility in production environments. Week 04: MLOps Fundamentals and Model Deployment Week 05: Building MLOps Pipelines Week 06: Monitoring and Performance Analysis in AI Systems Week 07: Learning Break Week 08: Project 01: Credit Default Risk Scoring
Module 03: LLMOps and Responsible AI Usage
This module focuses on operationalizing and responsibly using Generative and Agentic AI. It introduces LLMOps fundamentals, including CI/CD implementation and monitoring for LLMs, as well as the deployment of Agentic AI systems. The module also covers critical aspects of evaluating, securing, and ensuring responsible use of these AI systems. Week 09: LLMOps Fundamentals Week 10: LLMOps in Production Week 11: Agentic AI in Production Week 12: Evaluating and Securing Agentic AI Systems Week 13: Responsible AI and AIOps Adoption Week 14: Project 02: Agentic AI-Powered Retail Shopping Assistant
Note: The curriculum listed above are indicative and subject to updates as technology evolves.
Work on hands-on projects
Dive into hands-on projects to sharpen skills and build a unique portfolio
-
2
Hands-on projects
-
4
Real-world case studies
-
Emerging
Tools and technologies
FINANCIAL SERVICES
Credit Default Risk Scoring
Description
Build an MLOps pipeline to predict borrower default risk using financial and behavioral data.
Skills you will learn
- Pandas
- Scikit-Learn
- MLflow
- Random Forest
- XGBoost
- Model Deployment
- MLOps
- CI/CD
- Experimentation Tracking
- Python
RETAIL
Agentic AI-Powered Retail Shopping Assistant
Description
Develop an Agentic AI-powered shopping assistant that delivers personalized customer support by understanding intent, accessing data, and executing actions such as order tracking.
Skills you will learn
- Python
- Large Language Models
- Prompt Engineering
- LangChain
- OpenAI
- LangGraph
- Agentic AI
Note: The projects listed above are indicative and subject to updates to the curriculum.
Master in-demand AI & Agentic AI tools
Get trained on 20+ tools and techniques to enhance your workflow, optimize models, and build AI solutions
-
Python
-
OpenAI APIs
-
Scikit-Learn
-
LangChain
-
LangGraph
-
OpenAI
-
Pandas
-
ChatGPT
Note: The tools listed above are indicative and subject to updates as technology evolves.
Meet your faculty
Learn from renowned JHU faculty and build the expertise to implement and scale AI solutions across functions
-
Kiran Chittargi
Adjunct Faculty - Computer Science, Johns Hopkins University
Program Director at Microsoft
Global Expansion Lead for Azure
Know More
LinkedIn Profile
University LinkInteract with our mentors
Learn from seasoned AI mentors to apply concepts and build practical skills
-
Hassan Ayman
Senior Data Scientist, IBM
-
Tina Kovacova
Data Advisor, Kaggle
-
Arooj Ahmed Qureshi
Senior Manager AI Engineering, Bell
-
Ishwor Bhusal
Data Scientist - Supply Chain Data Innovation, Nissan Motor Corporation
Note: The mentors listed above are indicative and subject to change based on availability and scheduling.
Career Support
-
Resume Builder
Access to an AI-powered resume builder to create professional, impactful resumes aligned with targeted roles.
-
Mock Interviews
Unlimited mock interviews powered by AI to practice and refine interview skills.
What are the fees for the program?
The course fee is USD 2,100
Invest in your career
-
Learn to build, deploy, and operate AI and Agentic AI systems in real-world production environments
-
Add leading AI tools to an industry-ready portfolio to showcase skills and proficiency
-
Learn from AI experts in weekly live online sessions focused on real-world implementation
-
Receive a Certificate of Completion and 10 CEUs from Johns Hopkins University
Enrollment Process
Get started instantly with our self-enrollment process and begin your learning journey today
-
Enter your details
Provide your information to begin the enrollment process
-
Make payment
Complete the payment to receive your enrollment confirmation via email
Delivered in Collaboration with:
Johns Hopkins University is collaborating with online education provider Great Learning to offer the Certificate Program in AI & Agentic AI Engineering . This course leverages JHU's leadership in innovation, science, engineering, and technical disciplines developed over years of research, teaching, and practice. Great Learning collaborates with institutions to manage enrollments (including all payment services and invoicing), technology, and participant support. This email and other communications from Great Learning may contain customized links with your information. We recommend not sharing these emails and communications to prevent unintended data exposure.
