phone iconSpeak with our expert +14104988288

Delivered in collaboration with Great Learning

Learn more about the course

Get details on syllabus, projects, tools, and more

Name
Email
Mobile Number

By submitting this form, you consent to our Terms of Use & Privacy Policy and consent to be contacted via email, phone (including by AI-generated/pre-recorded voice calls), SMS, or WhatsApp.

No-Code Generative AI and Agentic AI

No-Code Generative AI and Agentic AI

Download Brochure
Apply Now

Application closes 18th Jun 2026

Why should you join this program?

  • List icon

    No-Code Program to Build AI Agents and Intelligent Workflows

    Build practical expertise in Generative AI and Agentic AI with Johns Hopkins University faculty and industry experts through real-world projects and case studies using no-code tools.

  • List icon

    Learn from JHU, a Leading US Research University

    Ranked #7 National University, #14 Best Global University, #2 in Computer Information Technology, reflecting JHU's leadership in research and innovation. (2026 Rankings)

overview icon

PROGRAM OUTCOMES

What will you learn to build and apply?

Through a structured learning journey, you will build the capability to:

  • List icon

    Understand key concepts in NLP, Generative AI, and Large Language Models (LLMs) through a no-code approach

  • List icon

    Understand the fundamentals of creating effective AI prompts in business scenarios

  • List icon

    Identify strategic business opportunities and industry use cases of GenAI and smart AI agents across sectors

  • List icon

    Understand Responsible AI principles, risks, ethics, and compliance challenges

  • List icon

    Understand AI agents, their evolution, and how they reason, act, use tools, and memory with real examples

  • List icon

    Understand how no-code tools and RAG enable AI workflows and connect AI with business data

Earn a Certificate of Completion from Johns Hopkins University

  • #7 National University Rankings

    #7 National University Rankings

    U.S. News & World Report, 2026

  • #2 Computer Information Technology

    #2 Computer Information Technology

    U.S. News & World Report, 2026

  • #14 Best Global University

    #14 Best Global University

    U.S. News & World Report, 2026

  • #1 Biomedical Engineering Program

    #1 Biomedical Engineering Program

    US News and World Report, 2026

KEY PROGRAM HIGHLIGHTS

Why Choose This Program?

  • List icon

    Learn from Johns Hopkins University Faculty

    Learn through recorded lectures and attend faculty-led masterclasses covering Generative AI, Agentic AI, AI governance, emerging AI trends.

  • List icon

    Interactive Mentorship by Industry Experts

    Learn from AI experts through mentorship sessions focused on practical applications, implementation challenges, and industry best practices.

  • List icon

    No-Code AI Curriculum

    Build practical expertise in Prompt Engineering, RAG, AI workflows, intelligent agents, and AI evaluation, without programming.

  • List icon

    Real-World Projects & Case Studies

    Work on projects and case studies across sales, healthcare, finance, HR, logistics, customer support, and operations using AI workflows and agents.

  • List icon

    Earn a Recognized Credential from Johns Hopkins University

    Earn a Certificate of Completion and 9 CEUs from Johns Hopkins University upon successful completion of the program.

  • List icon

    Personalized Program Support

    Receive guidance from a dedicated Program Manager and academic support from subject matter experts.

Skills you will learn

Retrieval-Augmented Generation (RAG)

Prompt Engineering

Natural Language Processing (NLP)

Multi-Agent Systems

Agent Orchestration

Agentic AI Systems

GenAI Workflow Automation

Sentiment Analysis

LLM Applications

Classification Modeling

Data Preprocessing

Exploratory Data Analysis

Rule-Based Validation

Retrieval-Augmented Generation (RAG)

Prompt Engineering

Natural Language Processing (NLP)

Multi-Agent Systems

Agent Orchestration

Agentic AI Systems

GenAI Workflow Automation

Sentiment Analysis

LLM Applications

Classification Modeling

Data Preprocessing

Exploratory Data Analysis

Rule-Based Validation

view more

  • Overview
  • Learning Journey
  • Curriculum
  • Projects
  • Tools
  • Certificate
  • Faculty
  • Mentors
  • Reviews
  • Fees
optimal icon

Who is the program for?

Professionals aiming to automate workflows and drive business impact with GenAI & Agentic AI via no-code tools

  • Business Leaders and Functional Heads

    Who need to automate enterprise-wide workflows, implement Agentic AI strategies, and drive organizational productivity without deep coding expertise.

  • Technology Professionals and Team Leads

    Who needs to rapidly prototype, evaluate, and orchestrate complex multi-agent systems and RAG pipelines using no-code platforms.

  • Subject Matter Experts

    Looking to ground AI in proprietary data, build specialized AI assistants, and enhance data-driven decision-making in high-stakes internal settings.

How is the program learning experience?

Our pedagogy is designed to ensure a holistic learning experience

  • banner-image

    Learn from Experts

    Learn from JHU faculty and industry experts to build skills in Generative AI and Agentic AI

  • banner-image

    Learn By Doing

    Apply Generative AI and Agentic AI concepts through hands-on projects and case studies

  • banner-image

    Earn a University Credential

    Earn a certificate of completion and 9 CEUs from Johns Hopkins University

  • banner-image

    Get Support Throughout the Learning Journey

    Program managers will help you stay on track, navigate key milestones & complete the program

What will you learn in the program?

The curriculum for the No-Code Generative AI and Agentic AI program is designed by the faculty of Johns Hopkins University and leading industry practitioners. It requires no prior programming experience and focuses on the architecture and orchestration of complex, trustworthy Agentic AI systems using no-code platforms and cutting-edge tools.

  • Masterclasses

    By JHU Faculty

  • Live Mentorship

    By Industry Experts

  • Self-Paced

    Modules

Pre-Work

This preparatory course introduces the role of no-code platforms such as n8n in building AI-powered workflows without programming. You will explore key components of n8n, including nodes, triggers, and integrations used to connect applications and services. The module also guides you in designing simple automated workflows to orchestrate tasks and integrate AI capabilities into business processes.

Concepts Covered

- Introduction to n8n - n8n Components - n8n Workflows

Course 1 | Gen AI and Agentic AI Foundations

This course introduces the fundamentals of Generative AI and Agentic AI, highlighting their evolution and real-world applications. Learners will explore practical frameworks and prompting techniques to effectively interact with AI systems and improve output quality, with a focus on accessible, no-code implementation.

Week 1 | Gen AI and Agentic AI Landscape

- Predictive AI vs. Gen AI vs. Agentic AI - The No-Code Revolution - Anatomy of an AI Model (Simplified) - The AI Stack: Models, Interfaces, and Orchestrators - Evolution of AI: From Chatbots to Autonomous Agents

Case-Study | Retail

Retail Order Query Chatbot Enable context-aware customer interactions for product queries and order tracking by integrating prompt engineering, LLMs, and AI agents to improve the shopping experience. Skills You Will Learn: Prompt Engineering, LLM Applications, Agentic AI Systems

Week 2 | Prompt Engineering 101

- The Intern Analogy - Advanced Frameworks: RTF vs. Chain of Thought - Context Injection - Iterative Prompting - Prompt Libraries - Avoiding Bias in Outputs

Case Study | Human Resources

RecruitSmart Design an LLM-powered recruitment screening system to extract structured insights from resumes, match candidates to job requirements, and generate consistent, explainable shortlisting decisions to improve hiring efficiency. Skills You Will Learn: Natural Language Processing, LLM Applications, Information Extraction

Course 2 | Building No-Code Gen AI Workflows

This course focuses on applying Generative AI to analyze and extract insights from unstructured business data. Learners will develop skills in prompt engineering, evaluating AI outputs, and building context-aware systems that integrate external knowledge sources. The course also covers techniques to improve reliability and connects AI models to real-world business data for practical applications.

Week 3 | Prompt Engineering and NLP Tasks

- Advanced NLP: Classification, Extraction, and Summarization - Content Generation: Zero-Shot vs. Few-Shot Prompting - Structural Output (Tables/CSV) - Language and Tone Control

Case Study | Finance

Credit Card Application Approval Prediction Organize credit card application data to improve accessibility and predict approval outcomes, enabling more efficient decision-making for financial institutions. Skills You Will Learn: Classification Modeling, Exploratory Data Analysis, Data Preprocessing

Week 4 | Evaluation of Gen AI Workflows

- Accuracy vs. Creativity Benchmarks - Hallucination Management: Fact-Checking and Grounding - Comparative Evaluation of AI Models - Bias Detection - Continuous Improvement Loops

Case Study | Finance

Stock News Sentiment Analysis Analyze stock news and price data to develop a sentiment analysis system that processes news articles, gauges market sentiment, and summarizes insights to support investment decision-making. Skills You Will Learn: Natural Language Processing, Sentiment Analysis, Text Summarization

Week 5 | Building Workflows on Proprietary Data with RAG

- Introduction to RAG - Document Chunking Strategies - Grounding AI in Private Data Sources and Citations - Data Privacy and Security

Case Study | Healthcare

Clinical Decision Support Assistant Enhance diagnostic efficiency and clinical decision-making by implementing a RAG-based system to retrieve medical knowledge from manuals and answer healthcare queries with evidence-based responses. Skills You Will Learn: Retrieval-Augmented Generation (RAG), Natural Language Processing, Prompt Engineering

Week 6 | Hands-On Project

Work on an industry-relevant project using in-demand tools and techniques, guided by expert mentors.

Week 7 | Learning Break

A learning break week for revision and preparation for upcoming modules.

Course 3 | AI Agents for Productivity

This course focuses on designing and managing autonomous AI agents to achieve defined goals. Learners will explore agent frameworks, build workflows with human oversight, and develop multi-agent systems for complex tasks. The course also covers performance optimization, cost efficiency, and implementing guardrails to ensure responsible and secure AI deployment.

Week 8 | Introduction to Agents

- The Agentic Mindset - Reasoning and Acting (ReAct Framework) - Tool Use and Function Calling - Agent Memory Systems - Triggers and Event-Driven Agents

Case Study | Finance

Reimbursement Automation Improve financial operations by leveraging AI to extract receipt details, categorize expenses, and validate reimbursement requests against company policies, reducing manual effort and errors. Skills You Will Learn: Information Extraction, Document Processing, Rule-Based Validation

Week 9 | Evaluating Agentic AI Workflows

- Trajectory Analysis - Permission Gates and HITL - Cost and Token Management - Success Rate Benchmarking - Bottleneck Identification

Case Study | Logistics

AI-Powered Shipment Disruption Router Improve logistics efficiency by implementing a multi-agent AI system that analyzes shipment disruptions, retrieves mitigation rules, and generates validated routing decisions with escalation for high-risk cases. Skills You Will Learn: Multi-Agent Systems, Retrieval-Augmented Generation (RAG), Workflow Automation

Week 10 | Multi-Agent Systems and Collaboration

- Multi-Agent Theory and Orchestration - Specialized Personas and Roles - Inter-Agent Communication Protocols - Conflict Resolution Strategies - Scaling Production with Parallel Agents

Case Study | Customer Support

AI Helpdesk Copilot Improve customer support efficiency by implementing an agentic AI system that classifies tickets, retrieves relevant knowledge, and generates policy-compliant responses with explainable reasoning and automated escalation. Skills You Will Learn: Agentic AI Systems, Retrieval-Augmented Generation (RAG), Prompt Engineering

Week 11 | Responsible AI

- Data Privacy and Prompt Security - AI Ethics: Fairness, Accountability, and Transparency - AI Governance and System Prompts - Jailbreaking Prevention - The Future of Pervasive Agentic AI

Case Study | Telecommunications

AI-Powered Telecom Policy Assistant Use natural language queries and guardrailed retrieval from policy documents to deliver accurate, compliant responses on plans, data limits, roaming rules, and refunds. Skills You Will Learn: Retrieval-Augmented Generation (RAG), Prompt Engineering, Natural Language Processing

Week 12 | Hands-On Project

Work on an industry-relevant project using in-demand tools and techniques, guided by expert mentors.

Anthropic Masterclass

This self-paced masterclass introduces the role of Anthropic and the capabilities of Claude models. You will explore concepts such as Constitutional AI, safety, and alignment, and apply effective prompting techniques to generate structured outputs. The masterclass also covers basic API usage, simple application development, model comparisons, and key ethical considerations in deploying AI systems.

Concepts Covered

- Introduction to Anthropic: Vision, Mission, and Role in the AI Ecosystem - Overview of Claude Models: Capabilities, Versions, and Use Cases - Constitutional AI: Principles and How It Differs from Traditional Alignment Approaches - Prompting Techniques with Claude: Best Practices for Effective Interactions - Safety and Alignment: Guardrails, Harmlessness, and Responsible AI Design - Working with Claude API: Setup, Authentication, and Basic Usage - Structured Outputs and Tool Use: Generating Reliable and Formatted Responses - Building Applications with Claude: Chatbots, Assistants, and Workflows - Comparing Claude with Other Models: Strengths, Limitations, and Positioning - Ethics and Responsible AI: Transparency, Bias, and Human-Centered Design

Self-Paced Module | Claude-Based AI Workflows

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 ~5 hours of structured learning.

Design and Execute AI Workflows

- Model selection and prompt engineering using Claude Chat - Agentic workflow design and orchestration using Claude CoWork - Plan → Approve → Execute → Iterate framework - Designing workflows with reasoning, tools, and multi-step execution - Applying concepts through real-world case studies

Build and Deploy AI Systems at Scale

- API integration and model usage using Claude Code - Tool integration using the Model Context Protocol - Designing agentic systems with memory, tools, and orchestration - Performance optimization, cost considerations, and system reliability - Responsible AI principles, including alignment approaches such as Constitutional AI

What projects will you work on?

Work on projects covering Prompt Engineering, RAG, AI agents, workflow automation, and AI governance

project icon

Operations

PolicyBot: Private Document RAG Assistant

Description

Create a “chat with your PDF” system to query internal manuals, connecting AI to company information and grounding responses in private data to address knowledge gaps.

Skills you will learn

  • Retrieval-Augmented Generation (RAG)
  • GenAI Workflow Automation
  • Document Extraction
  • Querying
project icon

Sales

Autonomous Multi-Agent Sales Intelligence System

Description

Orchestrate a virtual multi-agent system to automate B2B lead qualification, leveraging specialized agents to manage hand-offs, conduct research, and ensure secure approvals within an AI-driven workflow.

Skills you will learn

  • Multi-Agent Systems
  • Workflow Automation
  • Agent Orchestration

Which tools will you learn and apply?

Learn no code tools like Claude, Gemini, NotebookLM, and n8n to build AI workflows and intelligent agents

  • tools-icon

    ChatGPT

  • tools-icon

    n8n

  • tools-icon

    NotebookLM

  • tools-icon

    Gemini

  • tools-icon

    Claude

Earn a Certificate of Completion from Johns Hopkins University

Stand out in a competitive market with a Certificate of Completion in No-Code Generative AI and Agentic AI that validates the expertise developed through rigorous, practical assessments.

certificate image

* Image for illustration only. Certificate subject to change.

Who are the faculty for the program?

Learn from renowned JHU faculty and build the expertise to implement and scale AI solutions across functions

  • Dr. Ian McCulloh - Faculty Director

    Dr. Ian McCulloh

    Director of AI Executive & Professional Education, Johns Hopkins University

    Served as Chief Data Scientist and MD, AI, Accenture Federal Services

    Author of three books and over 100 peer-reviewed papers

    Know More
    Company Logo
  • Dr. Abhinanda Sarkar - Faculty Director

    Dr. Abhinanda Sarkar

    Senior Faculty & Director Academics, Great Learning

    30+ years of experience in data science, ML, and analytics.

    Ph.D. from Stanford, taught at MIT, ISI, and IIM Bangalore.

    Know More
    Company Logo

Who are the mentors for weekly live sessions?

Learn from seasoned AI healthcare mentors to apply concepts and build practical skills

  • Dr. Sunil Kumar Vuppala - Mentor

    Dr. Sunil Kumar Vuppala

    AI Partner, ArisGlobal
    Company Logo
  • Randhir Agarwal - Mentor

    Randhir Agarwal

    Director, Data Science & Data Engineering, Samsung Electronics
    Samsung Electronics Logo
  • Balachandra Deshpande - Mentor

    Balachandra Deshpande

    Head of Data Science, Enterprise Minds, Inc
    Enterprise Minds, Inc Logo
  • G Anthony Reina - Mentor

    G Anthony Reina linkin icon

    Head of Machine Learning, Stealth BioTech Startup
    Company Logo
  • Jeremy Samuelson - Mentor

    Jeremy Samuelson

    Executive VP, AI and Innovation, Integrated Quantum Technologies
    Company Logo

Course Fees

The course fee is USD 3,100

Invest in your career

  • benifits-icon

    Build practical skills in Generative AI, RAG, AI workflows, and intelligent agents through hands-on learning

  • benifits-icon

    Dedicate 8-10 hours weekly to faculty-led learning, industry mentorship, projects, and case studies

  • benifits-icon

    Learn from AI experts in weekly live online sessions focused on real-world implementation and business impact

  • benifits-icon

    Receive a Certificate of Completion and 9 CEUs from Johns Hopkins University

project icon

Easy payment plans

Avail our EMI options & get financial assistance

  • discount available

    SAVE200: USD 3,100 USD 2,900

Third Party Credit Facilitators

Check out different payment options with third party credit facility providers

affirm splitit

*Subject to third party credit facility provider approval based on applicable regions & eligibility

Take the next step

timer
00 : 00 : 00

Apply to the program now or schedule a call with a program advisor

Learn more about the program

Application closes: 18th Jun 2026

Apply Now

Application closes: 18th Jun 2026

Talk to our advisor for offers & course details

Schedule a call

Application Process

Applications close once the required number of participants enroll. Apply early to secure your spot

  • steps icon

    Fill the application form

    Apply by completing the online application form.

  • steps icon

    Application screening

    A panel from Great Learning will review your application to determine your fit for the program.

  • steps icon

    Join the program

    Receive an offer for a seat in the upcoming cohort of the program after a final review

Limited seats available

Build Smarter with AI

Apply Now

Batch Start Date

No-Code Generative AI and Agentic AI

Download Brochure
Apply Now

phone icon Application closes 18th Jun 2026

Got more questions? Talk to us

Connect with our advisors and get your queries resolved

Speak with our expert +14104988288 or email to office-gaaf-gl@jhu.edu

career guidance