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15th Oct 2026
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Application closes 15th Oct 2026
Learn from JHU faculty and industry experts to build end-to-end AI expertise across Machine Learning, Generative AI, and Agentic AI. Work on hands-on projects and case studies using AI tools.
Ranked #7 National University, #14 Best Global University, #2 in Computer Information Technology in 2026 by U.S. News & World Report, reflecting JHU's leadership in research and innovation.
PROGRAM OUTCOMES
Learn techniques to extract actionable insights and solve complex business challenges
Develop practical LLM workflows using prompt engineering, fine-tuning, RAG systems and AI agents.
Understand core AI concepts, identify problems, and associated ethical implications.
Understand NLP, GenAI, and experiment with models like Transformers & Stable Diffusion.
Construct and train neural networks and understand architectural differences.
Implement and evaluate supervised learning algorithms and anomaly detection techniques.
Apply key Python libraries to prepare data for analysis and modeling.
#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
Build end-to-end expertise in Machine Learning, Generative AI, and Agentic AI through recorded lectures and live masterclasses from renowned JHU faculty.
Learn from AI practitioners through live mentorship sessions focused on implementation, problem-solving, and real-world applications.
Progress from Python, data analytics, and Machine Learning to Generative AI, RAG, AI agents, and multi-agent systems.
Apply concepts through 5 hands-on projects and 30+ case studies spanning Machine Learning, GenAI, and Agentic AI applications.
Earn a Certificate of Completion and 16 CEUs from Johns Hopkins University upon successful completion of the program.
Access a dedicated program support team throughout your learning journey, and Academic Learning Support, which includes discussion forums and peer groups.
Skills you will learn
170 million
New roles to be created by 2030
Up to $ 165K
Median Annual Base Salary
$15.7 trillion
Projected economic value of AI by 2030
30% CAGR
Projected AI market growth
Build the skills to transition into AI & ML roles across US companies.
AI Engineer
Machine Learning Engineer
AI Research Scientist
Prompt Engineer
Big Data Engineer
NLP Engineer
Deep Learning Engineer
Business Intelligence Developer
AI Consultant
Computer Vision Engineer
For professionals across career stages looking to build AI expertise and lead transformative initiatives.
Tech Practitioners
Build hands-on capability in Machine Learning, Generative AI, and Agentic AI to design, evaluate, and deploy intelligent solutions
Aspiring AI Professionals
Learn AI, ML, GenAI, and Agentic systems to pivot into AI-focused roles by applying practical, Python-based learning to real-world business problems
Tech Innovators and Leaders
Build hands-on capability to design and orchestrate AI workflows using modern tools and frameworks to solve complex, real-world enterprise problems
Business Leaders and Functional Heads
Build practical AI fluency to identify opportunities and assess use cases to improve decision-making and drive business outcomes across functions
Our pedagogy is designed to ensure a holistic learning experience
Learn critical concepts through live masterclasses and recorded video lectures by JHU faculty
Clarify your doubts and gain practical skills during weekly live sessions with industry experts
Work on projects to apply the concepts & tools learnt in the module
Our dedicated program managers will support you through your learning journey
Certificate Program in AI and Agentic AI Engineering
Build autonomous, goal-driven AI agents capable of perceiving, reasoning, and acting independently.
Reach out to program advisor for more details.
*image for illustration purposes only.
The curriculum is designed by the faculty of Johns Hopkins University and leading industry practitioners. It helps you develop the human intuition and judgement that are critical to succeed in a tech career. It is taught by best-in-class professors, practicing industry experts, and professionals from leading global companies.
Self-paced
Modules
Live
Faculty-led masterclasses
Live
Mentorship sessions
This module will help learners navigate the AI landscape by identifying key problems and solution spaces, enabling businesses to leverage AI technologies effectively. Learners will acquire fundamental programming skills in Python to build AI solutions that support business initiatives and apply foundational concepts of probability and statistics to analyze data and inform strategic decision-making.
This module focuses on building a strong foundation in data analytics and applying the ROAD framework to identify and solve key business challenges using data-driven approaches. Learners will also utilize Python for data transformation and feature engineering to prepare datasets, and conduct exploratory and statistical analysis to uncover trends and patterns in data, enabling informed business decisions and strategic planning. Note: The module comprises one week of learning break and one week of project work.
This module focuses on building a strong foundation in core Machine Learning techniques by exploring supervised and unsupervised learning approaches and their real-world applications. It enables learners to model, classify, cluster, and detect patterns in data using algorithms such as linear regression, decision trees, K-means clustering, and anomaly detection techniques. Learners will also explore techniques for tuning and evaluating these models for optimizing predictive performance. Note: The module comprises one week of learning break and one week of project work.
This module builds a strong foundation in NLP and Generative AI for text-based applications to enhance communication and create innovative solutions. Learners will implement Prompt Engineering and Retrieval-Augmented Generation (RAG) techniques to improve response accuracy and relevance in AI-driven systems, and design and build Agentic AI workflows to automate tasks and optimize processes. Note: The module comprises one week of learning break and one week of project work.
This module focuses on advanced autonomous systems and provides a practical framework for designing, building, and deploying AI agents. Learners move beyond single-task LLMs to orchestrate multi-agent workflows, covering multi-agent system design, evaluation of Agentic AI workflows for accuracy and reliability, and pre-production and deployment of agents in real-world business environments. Note: The module comprises one week of learning break and one week of project work.
This module is designed to build practical capability in applying Generative AI and Agentic AI using the Claude ecosystem in real-world contexts. Participants build the ability to design, execute, and evaluate AI-driven workflows for real-world applications, supported by structured learning. *Disclaimer: Access to tools within the Claude ecosystem is not included as part of the program. Participants may choose to explore advanced capabilities independently.
This masterclass covers the Anthropic AI landscape, exploring Claude models, Constitutional AI, and key safety and alignment principles. Learners will apply effective Prompt Engineering techniques, use the Claude API for tasks and integrations, generate structured outputs, build simple applications, compare Claude with other AI models, and evaluate ethical considerations for deploying AI systems.
Apply your learning through real-world case studies guided by global industry experts. Please note: All case studies and projects outlined are indicative and subject to change.
Note: The curriculum listed above are indicative and subject to updates as technology evolves.
Gain practical, hands-on skills and leverage AI to solve business challenges.
Hands-on
projects
Real-world
case studies
In-demand
tools and techniques
AVIATION ANALYTICS
Description
Explore how to study aviation data to find patterns that help improve flight scheduling and operational efficiency.
Skills you will learn
HEALTHCARE
Description
Understand how to use EHR data and Machine Learning to support early intervention and deliver personalized care.
Skills you will learn
E-COMMERCE ANALYTICS
Description
Learn how to create a deep learning model that automatically tags clothing items based on their visual features to improve catalog management.
Skills you will learn
TRAVELTECH
Description
Understand how to design a personalized trip planner using Large Language Models (LLMs) and agentic AI to recommend destinations and create itineraries based on user preferences.
Skills you will learn
FINANCE
Description
Learn how to design an AI-driven underwriting system using multi-agent architectures to automate loan evaluation, improve decision consistency, and ensure compliance through risk analysis, policy retrieval, and human-in-the-loop review.
Skills you will learn
Note: The projects listed above are indicative and subject to updates to the curriculum.
Gain hands-on experience with 20+ tools and techniques like Python, Hugging Face, ChatGPT & more
Python
Pandas
NumPy
Scikit-Learn
Hugging Face
ChatGPT
ChatGPT API
Keras
Note: The tools listed above are indicative and subject to updates as technology evolves.
Stand out in a competitive market with the Certificate Program in Artificial Intelligence: Applied ML, GenAI, and Agents that validates the expertise developed through rigorous, practical assessments and CEUs.
* Image for illustration only. Certificate subject to change.
Learn from renowned JHU faculty and build technical intuition to make credible, strategic decisions.
Director, AI Executive & Professional Education, Johns Hopkins University
Served as Chief Data Scientist & MD of AI, Accenture Federal Services
Author of three books and over 100 peer-reviewed papers
.jpg "Dr. Anthony (Tony) Johnson")
Senior Professional Staff Member and Research Scientist, Applied Physics Laboratory, Whiting School of Engineering, Johns Hopkins University
Prominent academic leader overseeing innovative engineering programs.
Expert in robotics, data science, and advanced computing fields.
Senior Data Scientist - The Johns Hopkins University Applied Physics Laboratory
Expert in applied mathematics, computational epidemiology, and ML.
Over a decade of experience solving real-world problems with mathematical and AI tools.
.png "Dr. William Gray-Roncal")
Principal Research Scientist - Johns Hopkins University Applied Physics Laboratory
Expert in data science, neuroscience, AI, and precision medicine.
Leads cutting-edge research in brain network mapping and analysis.
Interact with dedicated and experienced AI experts who will guide you through your learning journey
Note: The mentors listed above are indicative and subject to change based on availability and scheduling.
Read our learners experience of the program support, faculty & mentors
I'm pleased to share that I recently completed the Program in Artificial Intelligence: Applied ML, GenAI, and Agents by Johns Hopkins University. Through hands-on projects in Generative AI, Machine Learning, Computer Vision, and Data Analytics, I developed solutions for real-world challenges across the energy, healthcare, finance, and aviation sectors. This journey strengthened my skills in Python and deep learning, as well as predictive analytics and data-driven decision-making. I look forward to applying these skills to create meaningful business impact. I would like to thank Johns Hopkins University and Great Learning for providing such an excellent learning experience. A special thanks to my teacher, Faraaz Sheriff, and my Program Manager, Nithin Raj, for their guidance and support throughout the program.
Read More
Synopsys
Jul 2026
Interact personally with industry professionals through career mentoring sessions to get valuable insights and guidance
Gain insights into what recruiters look for. Access career prep material and practice with AI-powered mock interviews.
Polish your resume using an AI-assisted builder to better showcase your skills and experience.
Build an industry-ready portfolio to showcase your mastery of skills and tools
The course fee is USD 3,700
Build end-to-end expertise in Machine Learning, GenAI, & Agentic AI through hands-on learning and application
8–10 hours weekly of self-paced videos, faculty masterclasses, industry mentorship, projects, and case studies
Attend weekly live online sessions with top industry mentors and build AI agents for business applications
Receive a Certificate of Completion and 16 CEUs from Johns Hopkins University
Easy payment plans
Avail our EMI options & get financial assistance
INSTALLMENT PLANS
Upto 12 months Installment plans
Explore our flexible payment plans
View Plans
Third Party Credit Facilitators
Check out different payment options with third party credit facility providers
*Subject to third party credit facility provider approval based on applicable regions & eligibility
Our registrations close once the requisite number of participants enroll for the upcoming batch. Apply early to secure your seat.
Register by completing the online application form.
A panel from Great Learning will review your application to determine your fit for the program.
After a final review, you will receive an offer for a seat in the upcoming cohort of the program.
Admission closing soon
What makes the Certificate Program in Artificial Intelligence from Johns Hopkins University different from other AI certificate courses?
The Certificate Program in Artificial Intelligence: Applied ML, GenAI, and Agents is designed to help
learners move beyond using AI tools to building AI-powered solutions. Unlike many AI courses
online that focus on a single topic, this Artificial Intelligence certificate program covers Applied
Machine Learning, Generative AI, Retrieval-Augmented Generation (RAG), AI Agents, and
Multi-Agent Systems through hands-on projects, case studies, and live faculty master classes.
Learners also earn a Certificate of Completion and 16 Continuing Education Units (CEUs) from
Johns Hopkins University upon successful completion.
How many hours per week does an AI certificate require?
This AI certificate program requires approximately 8–10 hours of learning per week, including
recorded content, live masterclasses by Johns Hopkins University faculty, mentorship sessions with
industry experts, and project work.
What is the best way to learn AI as an experienced professional?
For professionals looking to apply AI in real business scenarios, structured learning often provides
more value than relying solely on scattered online resources. This online certificate in Artificial
Intelligence combines expert instruction, hands-on projects, industry case studies, and guided
mentorship to help learners build practical AI capabilities across Machine Learning, Generative AI,
and AI Agents.
What certificate will I receive after completing this Artificial Intelligence program?
Upon successful completion, learners earn a Certificate of Completion from Johns Hopkins
University, along with 16 Continuing Education Units (CEUs) that recognize 160 learning hours.
How is this program delivered? Are the sessions live or recorded?
The program is delivered entirely online and combines both recorded and live learning. Recorded
video lectures form the core content delivery. Live masterclasses are conducted by Johns Hopkins
University faculty. Live mentorship sessions are held with industry experts. This blended format is
designed for working professionals who need schedule flexibility while still benefiting from expert-led
instruction and real-time interaction.
What career support does this program provide?
The program includes two Career Preparation Sessions focused on applying program skills for
professional advancement. Learners also receive access to an AI-powered resume builder, unlimited
AI-powered mock interviews, and curated interview preparation materials. Career resources are
designed to help learners translate program skills into readiness for AI-focused roles. The program
does not guarantee placement or employment outcomes.
Who teaches this program?
The curriculum is designed and taught by Johns Hopkins Whiting School of Engineering faculty.
Dr. Anthony (Tony) Johnson, a research scientist at the JHU Applied Physics Laboratory
Dr. Ian McCulloh, leading AI continuing education at Johns Hopkins
Dr. Shelby Wilson, a Senior Data Scientist with expertise in applied mathematics, computational
epidemiology, and Machine Learning.
Dr. William Gray-Roncal, a Principal Research Scientist specializing in data science,
neuroscience, AI, and precision medicine.
In addition to faculty, learners receive live mentorship from industry experts at organizations
including Apple, US Bank, RBC Capital Market, and Moveworks.
What does the curriculum cover in this program?
The curriculum is structured across four core modules plus pre-work and self-paced electives.
Pre-work covers the AI landscape, Python fundamentals, and probability and statistics.
Module 1 covers Python for data analytics and feature engineering.
Module 2 addresses Applied Machine Learning, including supervised learning, classification,
clustering, and anomaly detection.
Module 3 covers Generative AI for Natural Language Processing, including Prompt Engineering
and Retrieval-Augmented Generation (RAG).
Module 4 focuses on building and deploying multi-agent AI systems.
Additional self-paced modules cover Model Deployment, Reinforcement Learning,
Recommender Systems, and Dimensionality Reduction.
Does the curriculum include Machine Learning application development?
Yes. Learners build practical applications throughout the program, covering data preparation,
predictive modeling, LLM workflows, AI agent design, Retrieval-Augmented Generation, deployment
concepts, and Multi-Agent Systems that mirror enterprise AI use cases.
Does this program include hands-on projects?
Yes. Learners complete five hands-on projects and work through 30+ industry case studies spanning
healthcare, finance, retail, aviation, travel, marketing, and other domains to build a portfolio
demonstrating practical AI skills.
What are some Machine Learning application examples included in the program?
Projects include healthcare prediction systems, intelligent fashion tagging, travel planning with
Agentic AI, mortgage underwriting using multi-agent architectures, flight delay analysis, retail
chatbots, and agricultural yield forecasting. These examples demonstrate how Machine Learning
and Generative AI solve real business problems across industries.
Why are AI Agents becoming important for enterprises?
AI Agents extend beyond traditional chatbots by reasoning, planning, using tools, retrieving
information, and completing multi-step tasks. As enterprises automate increasingly complex
workflows, AI Agents help improve productivity, decision-making, and operational efficiency. This
program teaches learners how to build, evaluate, and deploy Agentic AI workflows and multi-agent
systems for real-world business applications.
Does this program cover Retrieval-Augmented Generation (RAG)?
Yes. Retrieval-Augmented Generation (RAG) is covered in Module 3. Learners will implement and
analyze RAG systems to improve language model performance by retrieving contextually relevant
information and generating more accurate responses. The program also lists implementing and
analyzing RAG systems as a core learning outcome.
Does this program include a module on Claude and Anthropic AI?
Yes. The curriculum includes a dedicated Claude-Based AI Workflows module, supported by
approximately 5 hours of structured learning. It covers model selection and Prompt Engineering
using Claude Chat, agentic workflow design using Claude CoWork, and API integration using Claude
Code. The module also addresses the Model Context Protocol (MCP), Constitutional AI and
responsible AI principles, and performance optimization for agentic systems.
An Anthropic Masterclass is also included, covering Claude models, AI safety principles, and ethical
considerations for AI deployment.
Note: Claude API access is not included in the program fee; learners may explore advanced usage
independently.
What tools and technologies are covered in this program?
The program covers Python, Pandas, NumPy, scikit-learn, TensorFlow, Keras, OpenCV, Hugging
Face Transformers, LangChain, LangGraph, OpenAI API, Streamlit, and Claude. Learners receive
access to OpenAI API keys from Great Learning for supported learning activities. The curriculum
also covers the Model Context Protocol (MCP) for tool integration in agentic systems.
Is prior Machine Learning experience required for this certificate program in Artificial Intelligence?
No extensive Machine Learning background is required. The curriculum begins with Python,
probability, statistics, and data analytics before progressing to Applied Machine Learning, Generative
AI, and Agentic AI, helping learners build knowledge step by step.
Can I build AI solutions without coding?
While the program introduces Python programming because it is essential for developing AI
applications, it follows an application-oriented approach that helps learners gradually build practical
skills. Through guided projects and mentorship, participants learn how to create AI-powered
solutions rather than simply studying theory.
Is this program relevant for business leaders and non-technical professionals?
Yes. Business Leaders and Functional Heads are one of the four target audiences this program is
explicitly designed for. The curriculum is structured to build practical AI fluency, including how to
identify high-impact AI use cases, evaluate AI solutions, and understand responsible AI practices.
Non-technical learners benefit from the application-oriented curriculum, structured mentorship, and
real-world case studies that connect AI concepts to measurable business outcomes.
What is the fee for the Certificate Program in Artificial Intelligence?
For information on fee structure, offers, payment plans, and eligibility for financial assistance, contact your Program Advisor.
What does the program fee include?
The program fee covers access to the online learning platform, recorded lectures, live Johns
Hopkins University faculty masterclasses, mentorship sessions with industry experts, projects,
case studies, learner support, and program completion requirements. Great Learning also
provides OpenAI API keys for supported learning activities.
Disclaimer: Claude API access is not included as part of the program. Learners may
explore advanced usage independently
Does the program include learning support throughout the course?
Yes. Learners receive guidance from a dedicated Program Manager, academic support, peer
discussion forums, project communities, and AI-assisted learning support throughout the program
How can this Artificial Intelligence certificate program help me advance my career?
The program develops practical skills in Applied Machine Learning, Generative AI, AI Agents,
and LLM-powered applications, enabling professionals to contribute to AI initiatives, automate
business processes, develop intelligent applications, and support enterprise AI adoption. The
hands-on projects and Johns Hopkins University credential can also strengthen your
professional portfolio.
How is this Johns Hopkins AI course relevant for professionals building enterprise AI solutions?
The curriculum emphasizes practical implementation through predictive analytics, LLM
applications, Retrieval-Augmented Generation, AI Agents, and Multi-Agent Systems. By working
on real-world business use cases, learners gain experience that aligns with how organizations
are increasingly adopting AI across functions.
How should leaders prepare their organizations for AI adoption?
Leaders should build AI literacy, identify high-impact business use cases, understand
responsible AI practices, and develop the capability to evaluate AI solutions before
implementation. This program helps professionals build both technical understanding and
practical judgment through real-world AI applications, case studies, and Agentic AI workflows
Can this Johns Hopkins AI certificate help me build an AI portfolio?
Yes. Learners complete five projects, solve 30+ case studies, and create an industry-ready
e-portfolio demonstrating their ability to build AI solutions using modern tools and techniques.
This portfolio can be valuable when applying AI skills in current or future roles.
Johns Hopkins University is collaborating with online education provider Great Learning to offer the Certificate Program in Artificial Intelligence: Applied ML, GenAI, and Agents. Great Learning is a professional learning company with a global footprint in 14+ countries. Its mission is to make professionals around the globe proficient and future-ready. This program leverages JHU's leadership in innovation, science, engineering, and technical disciplines developed over years of research, teaching, and practice. Great Learning manages the enrollments and provides industry experts, student counselors, course support, and guidance to ensure students get hands-on training and live personalized mentorship on the application of concepts taught by the JHU faculty.
Application Closes
15th Oct 2026
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