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No-Code Generative AI and Agentic AI

No-Code Generative AI and Agentic AI

Application closes 23rd Apr 2026

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PROGRAM OUTCOMES

Become an AI-powered professional

Drive business value through the strategic implementation of AI technologies

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

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    Understand the fundamentals of creating effective AI prompts in business scenarios

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

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

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

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    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

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    Learn from a top-ranked university

    Learn from expert JHU faculty and industry leaders.

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    Hands-on learning

    Drive business value by strategically applying Generative AI and AI Agents through a no-code approach, hands-on projects, and real-world case studies.

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    Industry-focused curriculum

    The curriculum covers key areas such as NLP, Generative AI, Large Language Models, Prompt Engineering, Agentic AI, and Responsible AI.

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    Live masterclasses and mentorship

    Experience live mentorship by industry experts and live faculty-led masterclasses for structured, personalized learning.

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    Learning support

    Get unique academic support through the Great Learning community, project discussion forums, and peer groups for a comprehensive learning experience.

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    Dedicated support

    Access a dedicated Program Manager who will assist you through your learning journey to ensure you achieve your learning objectives.

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
  • Fees
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This program is ideal for

The program requires no programming knowledge and will be especially relevant to:

  • Functional Professionals

    In sales, marketing, operations, research and consulting, finance, legal, product, and other functions

  • Enthusiasts

    Anyone new to AI Agents & Generative AI who wants to boost productivity and drive business value

  • Technology Professionals

    Interested in understanding and applying AI, including team leads and managers looking to integrate AI into workflows and guide their teams

  • Business Analysts

    Including strategy professionals seeking actionable insights from AI

Experience a unique learning journey

Our pedagogy is designed to ensure a holistic learning experience

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    Learn from world-renowned faculty

    Learn critical concepts through live masterclasses and recorded video lectures by JHU faculty

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    Work on hands-on projects

    Work on projects to apply the concepts & tools learnt in the module

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    Engage with your mentors

    Clarify your doubts and gain practical skills during weekly live sessions with industry experts

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    Get personalized assistance

    Our dedicated program managers will support you through your learning journey

Curriculum

The curriculum for 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 is taught by best-in-class faculty and industry experts.

  • 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.

Self-Paced | Anthropic Series 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

Work on hands-on projects and case studies

Engage in hands-on activities in Finance, Marketing, Ops, HR, and Consulting, using emerging tools.

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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
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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
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RETAIL

Retail Order Query Chatbot

Description

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
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HUMAN RESOURCES

RecruitSmart

Description

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
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FINANCE

Credit Card Application Approval Prediction

Description

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
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FINANCE

Stock News Sentiment Analysis

Description

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
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HEALTHCARE

Clinical Decision Support Assistance

Description

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
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FINANCE

Reimbursement Automation

Description

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
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LOGISTICS

AI-Powered System Disruption Router

Description

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
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CUSTOMER SUPPORT

AI Helpdesk Copilot

Description

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
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TELECOMMUNICATIONS

AI-Powered Telecom Policy Assistant

Description

Use natural language queries and guardrail 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

Learn in-demand tools and techniques

Learn to leverage no-code platforms to build AI-powered workflows to drive better business outcomes

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    n8n

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    NotebookLM

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    Gemini

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    OpenAI APIs

Earn a certificate of completion from Johns Hopkins University

Earn 6.5 Continuing Education Units (CEUs) upon program completion

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* Image for illustration only. Certificate subject to change.

Meet your faculty

Learn from world-renowned faculty with in-depth expertise in AI, neuroscience, and applied analytics

  • Dr. Christophe Morin  - Faculty Director

    Dr. Christophe Morin

    Lecturer, Whiting School of Engineering, Johns Hopkins University

    Pioneer in neuromarketing, author of The Persuasion Code, and expert in AI-driven marketing.

    Developed the NeuroMap™ model and brain-based persuasion tools used globally.

    Know More
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  • Dr. Jane Pinelis  - Faculty Director

    Dr. Jane Pinelis

    Chief AI Engineer, AIS Branch, Johns Hopkins University

    Leads AI scientists at Johns Hopkins University Applied Physics Laboratory

    Author of The Experiment of a Lifetime on women in Marine combat roles

    Know More
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  • 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
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Interact with our industry mentors

Interact with dedicated mentors who are current practitioners and experts in Generative AI and Agentic AI

  •  Bridget Huang-Gregor  - Mentor

    Bridget Huang-Gregor linkin icon

    GenAI/ML Engineer at Amazon Web Services (AWS)
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  •  Tanya Glozman  - Mentor

    Tanya Glozman linkin icon

    Applied Science - AI/ML, Apple
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  •  Michael Lively  - Mentor

    Michael Lively linkin icon

    Founder, QuantumAI
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Course Fees

The course fee is USD 3,100

Invest in your career

  • benifits-icon

    Understand key concepts in NLP, Generative AI, and Large Language Models (LLMs).

  • benifits-icon

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

  • benifits-icon

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

  • benifits-icon

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

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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

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

Take the next step

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

Learn more about the program

Application closes: 23rd Apr 2026

Application closes: 23rd Apr 2026

Talk to our advisor for offers & course details

Application Process

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

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    Fill the application form

    Apply by completing the online application form.

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    Application screening

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

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    Join the program

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

Batch start date

  • USA & Canada · 23rd May 2026

    Admission closing soon

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

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