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Top Rated Data Science Program at University of Texas at Austin

Certificate Program in Applied Generative AI

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Application closes 28th Aug 2025

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  • Program Overview
  • Curriculum
  • Projects
  • Certificate
  • Faculty
  • Reviews
  • Fees
  • FAQs

Why choose the online Applied Generative AI course

  • highlight-icon

    Curriculum designed & delivered by JHU faculty

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    Monthly live online masterclasses by JHU faculty

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    Weekly live mentored learning sessions in small groups

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    Work on 2 Hands-on Projects and 6+ real-world case studies

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    Personalized assistance from a dedicated program manager

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    Certificate of Completion from Johns Hopkins University

Globally trusted by 9 million learners

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    Best Global University

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Skills you will learn

  • Prompt Engineering
  • Solving Natural Language Problems
  • Building Generative AI Workflows
  • Python for Artificial Intelligence
  • Ethical AI Practices
  • Evaluating Generative AI Solutions
  • Fine-tuning LLMs
  • Agentic AI Development
  • Secure AI Development

About the Applied Generative AI Program

The certificate program in Applied Generative AI is a comprehensive 16-week online course designed for professionals eager to leverage Generative AI to solve business challenges and drive innovation within their organizations.

Program Features:

  • Live Masterclasses with JHU Faculty:Participate in monthly live sessions led by Johns Hopkins University faculty, which offer the latest insights and practical guidance on AI strategy.
  • Weekly Mentored Learning Sessions:Develop proficiency in using Generative AI for a variety of practical scenarios by participating in interactive, mentor-led sessions where industry experts present case studies and provide deep insights into AI applications in business.
  • Generative AI Applications and Workflow Automation:Gain expertise in Generative AI, learning how to design automated workflows and build AI applications that address business needs.
  • Dedicated Program Support:Access to academic learning support, a dedicated program manager and peer groups through discussion forums for a comprehensive learning experience.
  • Certificate of Completion and 10 CEUs from JHU:Upon successful completion, earn a prestigious certificate and 10 CEUs from Johns Hopkins University, recognizing your proficiency in Generative AI

This program blends theoretical foundations with hands-on experience, equipping participants with the skills and knowledge to implement Generative AI solutions and lead AI-driven initiatives in their organizations.

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Why enroll in an Applied Generative AI course?

Generative AI is Revolutionizing Business Solutions 

Generative AI is transforming industries by automating creative tasks, enhancing customer experiences, and optimizing business processes. According to a Gartner report, more than 80% enterprises will have used Generative AI APIs or deployed Generative AI-enabled applications by 2026. This rapid adoption underscores the urgent need for professionals who can design and implement AI solutions, positioning them at the forefront of this AI-driven transformation. 


Gain Practical Skills to Build and Deploy Generative AI Solutions 

This program emphasizes hands-on learning, equipping you with the technical skills needed to create and implement AI solutions for business challenges. Whether you're a technology professional, data professional, technology consultant, technical manager or a STEM graduate, you’ll learn to work with Large Language Models (LLMs). The curriculum combines theory with practical case studies, enabling you to apply Generative AI in your workplace immediately. 


Bridge the Generative AI Talent Gap 

Despite the widespread adoption of AI, there is a growing shortage of professionals skilled in Generative AI technologies. This gap presents a lucrative opportunity for those with expertise in designing AI models. By completing this program, you'll gain the in-demand skills that businesses are actively seeking, making you a preferred candidate for potential employers. 


Work on Hands-on Projects and Case Studies 

In addition to theoretical knowledge, the program offers practical experience through hands-on projects and case studies under the guidance of industry experts. You’ll work on practical business problems, giving you insights that are directly applicable to the industry.

Who is this program for?

This program is designed for individuals looking to explore how Generative AI can solve real-world business problems. 


Technology Professionals: 

Professionals who want to learn and apply Generative AI, enabling them to build and deploy AI-driven solutions at work or for personal projects using OpenAI and open-source LLMs. 


Data Professionals: 

Data Analysts, Data Engineers, and Data Scientists seeking to enhance their ability to interpret and analyze data through Generative AI, uncovering deeper insights and expanding their expertise in text generation, image processing, and data analysis. They will also learn to deploy Generative AI solutions and strengthen their AI model development and data system maintenance abilities. 


Technology Consultants and Technical Managers: 

Professionals who want to understand Generative AI, implement best practices, manage risks and ethical considerations, and guide technical teams to design and develop advanced AI solutions for their employers and clients. 


STEM (Science, Technology, Engineering, and Mathematics) Graduates: 

Professionals who are graduates from science, technology, engineering, and mathematics fields wishing to upskill through hands-on training in Generative AI and become part of a cutting-edge industry with significant growth potential.

What are the key learning outcomes of this Applied Generative AI Program?

The key learning outcomes of this course are: 


  • Understand the theoretical foundations of generative AI and its applications 
  • Develop and train generative models using contemporary machine learning frameworks. 
  • Apply generative AI techniques to create text, image, and multimedia content. 
  • Evaluate the ethical implications of Generative AI 
  • Implement best practices to mitigate potential risks in Generative AI solutions 
  • Critically analyze the impact of generative AI on various industries and society as a whole.

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Comprehensive Curriculum

The Applied Generative AI program curriculum is designed by the faculty of JHU, Great Learning, and leading industry practitioners. The program modules are taught by the best-in-class professors and practicing industry experts. The objective of the course is to acquaint the learners with the skill of solving problems and deploying Generative AI solutions for various business applications.

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Pre-work

This program starts with the prework module that aims at providing all the necessary tools for your learning journey. It establishes a solid foundation in AI and its applications.

Module 1: Learning Python with Generative AI

This module provides a comprehensive introduction to Python programming fundamentals, with a focus on Generative AI. It offers a solid understanding of Generative AI techniques like Large Language Models (LLMs) and Generative Adversarial Networks (GAN’s).

Week 1: Generative AI Landscape

In the first week, you will start learning the key concepts of Generative AI, how LLMs function, what’s under the hood, and why they behave the way they do. The week will conclude with exploring the business applications of Generative AI across industries and functions like Marketing, Healthcare, and Productivity.

Week 2: Python Programming with Generative AI - Part 1

This week, you will learn how to use Generative AI models to generate code for simple Python-based applications, like a calculator or a database. During the week, you will learn how to ask Chat GPT for a lesson, create code, interpret, debug, etc.

Week 3: Foundation of AI

This week, you will learn the fundamentals of Machine Learning, which are essential to grasp at an intuitive level how LLMs work. You will also learn how to build ML classifiers using Generative AI and evaluate various machine learning models using Generative AI.

Week 4: Python Programming with Generative AI - 2

This week, you will learn how to interact with Generative AI using AI libraries. You will explore how to interface and work with different types of text and data modalities in Python. Building on last week, you will learn how to use Generative AI to store and manipulate text, read files, and clean text data in Python.

Module 2: Generative AI for Business Productivity

This module offers an opportunity to learn how to use Generative AI for enhancing business productivity and solving business problems. You will explore techniques such as text summarization, text classification, and text generation through prompting or Prompt Engineering with LLMs.

Week 5: Natural Language Processing And Image Classification

This week, you will learn how to address fundamental text-based challenges, including sentiment analysis, topic modeling, and named entity recognition, through practical business case studies.

Week 6: Transformers for Large Language Models

This week, you will understand the foundational concept behind how Large Language Models (LLMs) work, specifically focusing on ‘self-attention’. Additionally, you will learn about the building block of LLMs, the ‘Transformer’. Throughout the week, you will also learn how to solve text-based problems using Transformers.

Week 7: Prompt Engineering

This week, you will explore the fundamentals of Prompt Engineering and prompting techniques to help you write effective prompts to obtain specific responses from an LLM for business use cases. You will learn about LLM training and development, and model deployment. Additionally, you will discover how to build practical workflows to automate problem-solving with LLMs using LangChain.

Week 8: Classification, Content Generation, and Summarization with Gen AI

This week, you will focus on addressing common issues in text processing, including summarization, content generation, and classification, in the context of Generative AI. Additionally, you will learn how to assess the quality of these solutions using objective metrics and other LLMs.

Week 9: Project-1 (Sample Business Problem)

This week, you will be involved in a project. This project will be focussed on developing an AI-powered ‘secretary’ that assists users in managing emails more efficiently by highlighting the most urgent messages, summarizing email threads, and improving overall productivity. The project aims to leverage Generative AI models for classifying, prioritizing, and summarizing emails to provide concise, actionable insights for users.

Week-10: Learning Break

Module 3: Designing Advanced Generative AI Workflows

This module will focus on building and deploying advanced Generative AI solutions and agents using Retrieval-Augmented Generation (RAG) and fine-tuned Large Language Models (LLMs). You will learn to implement these technologies securely and responsibly for both private and public applications.

Week 11: Secure and Responsible Gen AI Solutions

This week, you will be able to identify and mitigate bias and risk in AI systems, while also understanding and applying relevant laws and regulations for the responsible usage of AI.

Week 12: Developing Agents with LangChain

This week, you will learn how to build Agentic Generative AI workflows with LangChain and create practical agents, such as Web and Database agents. Throughout this process, you will learn about the LangChain library, AI agents, their types, and workflows.

Week 13: Retrieval Augmented Generation (RAG) Search

This week, you will understand the roles and differences between embeddings and tokenization in LLMs. Learn the importance of Byte-Pair Encoding, gain insights into computing and applying sentence embeddings, explore how RAG improves response accuracy, and learn about the algorithms behind LLM embeddings and their impact on performance.

Week 14: Advanced RAG

This week, you will be able to differentiate between simplicity and depth in RAG implementations, fine-tune a basic RAG model, and evaluate RAGs effectively.

Week 15: Fine-Tuning and Customization of Generative AI

This week, you will learn how fine-tuning works. Explore different fine-tuning methods, and see how to adjust an open-source LLM for real-world business uses.

Week 16: Project-2 (Sample Business Problem)

This week, you will get another project. In this project, you will develop a secure, fine-tuned Retrieval-Augmented Generation (RAG) system that enhances search capabilities on a personal computer, allowing users to retrieve relevant information from personal files and documents quickly and accurately. The project will emphasize ensuring data privacy, mitigating bias, and personalizing the RAG model for specific use cases. 


Note: Curriculum, projects, and tools are under the purview of JHU and can be updated as per industry requirements

Note: Curriculum, projects, tools are under the purview of JHU and can be updated as per industry requirements

In-demand tools and libraries

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    Python

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    Google Colab

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    BERT

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    Vector Database (Chroma / Pinecone)

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    RAG (Retreival Augmented Generation)

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    Quick Fine-Tuning Techniques

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    VS Code

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    Transformers

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    Llama

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    Gradio

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    ChatGPT

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    Open AI

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    Whisper

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    Scikit-learn

    • Note: Libraries and tools used are under the purview of the faculty and a thorough review would be undertaken from time to time to ensure the programme coverage is in line with industry requirements.

Work on real-world case studies

Transform theoretical knowledge into tangible skills by working on multiple hands-on exercises under the guidance of industry experts.

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Finance

Predict Loan Default Cases

Build a predictive model to identify high-risk loan applicants. Use structured evaluation to reduce subjectivity in approvals and flag potential defaults based on credit scores and loan types.

Skills Used: Python, model building, evaluation
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Sports Analytics

Sentiment Analysis on Social Media for NFL Player Draft

Analyze Reddit discussions around NFL Draft picks using NLP. Automate sentiment classification to extract insights for teams and analysts and support data-driven draft decisions

Skills Used: Tokenization, embedding, model building
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E-commerce

E-commerce Chatbot for Order Management

Improve customer support by deploying an AI-powered e-commerce chatbot built with responsible AI principles. Optimize response efficiency, reduce operational costs, and ensure fair, transparent, and secure user interactions.

Skills Used: Open AI, Prompt Injection, Toxicity, Llama Guard, PII protection, PII masking, Gradio
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Enterprise Software

Salesforce CRM Q&A Assistant

Empower internal sales teams by implementing a RAG-powered CRM assistant. Optimize information retrieval to deliver instant, context-aware support, improving workflow efficiency and ensuring consistent, accurate responses.

Skills Used: Embeddings,Tokenization, Retrieval Augmented Generation, RAGAs
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Healthcare

Multi-Modal RAG for Healthcare

Boost user engagement by launching a multimodal RAG-based AI system for personalized healthcare support. Optimize response relevance with text-and-image integration, enhancing trust and conversion in the wellness sector.

Skills Used: Retriever with metadata, Prompt Enhancement/ Query Expansion, Multimodal RAG

Note: *This is a tentative list and is subject to change.

Earn a Johns Hopkins University Certificate in Applied Generative AI

Enhance your professional credentials with a certificate in Applied Generative AI from Johns Hopkins University. Share your achievement with your network and elevate your career in the rapidly evolving AI landscape.

Johns Hopkins University Certificate

* Image for illustration only. Certificate subject to change.

  • Best Global University

    Best Global University

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  • National University Rankings

    National University Rankings

    U.S. News & World Report

For any feedback & queries regarding the program, please reach out to us at office-appl-genai-gl@jhu.edu

Learn from world-renowned faculty

When you choose the Applied Generative AI Program from Johns Hopkins University, you gain access to world-class coaching from renowned faculty and industry experts.

  • Dr. Ian McCulloh - Faculty Director

    Dr. Ian McCulloh

    Manager, AI Continuing and Exec Ed, Johns Hopkins University

    Dr. Ian McCulloh leads the Artificial Intelligence portfolio for Lifelong Learning at Johns Hopkins University, with faculty roles in Computer Science and Public Health. His research combines AI, neuroscience, and human behavior to create scalable AI systems that improve access to products, services, and healthcare. Previously, he was Accenture’s Chief Data Scientist, where he built and led a 1,200-strong Federal AI practice delivering advanced AI solutions for the U.S. Government. A retired U.S. Army Lieutenant Colonel, Dr. McCulloh founded the West Point Network Science Center and served as Chief Strategist for Information Warfare at CENTCOM. He holds a Ph.D. in Computer Science from Carnegie Mellon University and has authored several significant publications, including over 100 peer-reviewed papers.

    Read more

  • Dr. Pedro Rodriguez - Faculty Director

    Dr. Pedro Rodriguez

    Faculty Member, Johns Hopkins University

    Dr. Pedro Rodriguez leads the Information Science Branch at Johns Hopkins Applied Physics Laboratory, overseeing 250+ AI/ML researchers. He has led critical AI projects for the Department of Defense and received recognition from Time Magazine for his contributions to public health. Dr. Rodriguez holds a Ph.D. in Electrical Engineering and an M.S. in Biomedical Engineering.

    Read more

  • Dr. Iain Cruickshank - Faculty Director

    Dr. Iain Cruickshank

    Faculty Member, Johns Hopkins University

    Dr. Iian Cruickshank holds faculty appointments in Computer Science at Johns Hopkins and Carnegie Mellon University. He specializes in machine learning and AI for the U.S. Army, with research focused on online misinformation and machine-learning systems. Dr. Cruickshank holds a Ph.D. in Societal Computing from Carnegie Mellon.

    Read more

  • Dr. Pavankumar Gurazada - Faculty Director

    Dr. Pavankumar Gurazada

    Senior Faculty, Academics, Great Learning

    Dr. Pavankumar Gurazada brings a unique blend of industry experience and academic expertise, specializing in marketing, digital marketing, and machine learning. He is also a Data Science advisor and board member of Constems AI, a deep tech startup focused on building computer vision systems for Industry 4.0. Dr. Gurazada completed his Ph.D. from IIM Lucknow, with a research focus on using machine learning techniques to understand consumer engagement on social media. His research has been presented at prominent international conferences such as the EMAC Conference 2018, the China Internet+ Innovation and Entrepreneurship Conference 2019, and the NASMEI and MRSI conferences. His book, Marketing Analytics, published by Oxford University Press in March 2021, is a testament to his expertise in the field. He holds an MBA from IIM Bangalore and an Integrated Master’s degree in Science from IIT Bombay. With a career that spans roles in retail and B2B sales management, Dr. Gurazada’s industry experience includes leadership positions at Alghanim Retail in Kuwait and Saint Gobain in UAE & Oman, where he significantly contributed to business growth and managed distribution networks.

    Read more

Our Mentors

  • Jeremy Samuelson - Mentor

    Jeremy Samuelson

    Principal Data Scientist & ML Engineer, Equifax
  • Bhaskarjit Sarmah - Mentor

    Bhaskarjit Sarmah

    Head RQA AI Labs, BlackRock
  • Tanya Glozman - Mentor

    Tanya Glozman

    Applied Science - AI/ML, Apple
  • Bridget Huang-Gregor - Mentor

    Bridget Huang-Gregor

    Tech Lead Engineering , Capital One

Note: This is an indicative list and is subject to change based on the availability of faculty and mentors

Program Fee

Program Fees: 2,950 USD

Apply Now
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Easy payment plans

Avail our EMI options & get financial assistance

  • discount available

    Upfront discount:2,950 USD 2,800 USD

    Referral discount:2,950 USD 2,800 USD

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

Benefits of learning with us

  • Program designed by JHU faculty
  • 2 hands-on projects and 6+ real-world case studies
  • Live mentored learning in micro classes
  • Live sessions with industry experts
  • Flexible learning approach

Application process

Our admissions close once the requisite number of participants enroll for the upcoming batch . Apply early to secure your seats.

  • steps icon

    1. Fill application form

    Apply by filling a simple online application form.

  • steps icon

    2. Interview Process

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

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    3. Join program

    After a final review, you will receive an offer for a seat in the upcoming cohort of the program.

Limited seats available

Apply now to harness Generative AI for business innovation

Apply Now

For any queries or in case of unsatisfactory response reach out to us at office-appl-genai-gl@jhu.edu

Batch Start Date

  • Online · 13th Sep 2025

    Admission closing soon

    Apply Now

Frequently asked questions

Program Details

What is the Generative AI course offered by Johns Hopkins University?

This is a certificate program in Applied Generative AI, offered by Johns Hopkins University. This 16-week online program is designed to equip professionals with advanced skills in Generative AI. This Applied Generative AI Program includes theoretical foundations with practical case studies on cutting-edge topics like Large Language Models, Natural Language Processing, and Retrieval Augmented Generation.

What are the highlights of the Generative AI course?

The Applied Generative AI Program from Johns Hopkins University is a transformative online learning program that equips professionals with advanced skills in Generative AI. Here are some of the highlights of the program: 


Online Format: The program is delivered online, with classes conducted through interactive live mentorship and recorded video lectures. You will receive monthly live masterclasses by JHU faculty. 


World-class faculty: The course is taught by world-class faculty and experts who have real-world experience leading AI practices at Fortune 500 companies. 


Research-driven curriculum: The comprehensive curriculum of the Gen AI program ensures that the learners gain the most up-to-date knowledge. 


In-demand tools and libraries: JHU’s incomparable curriculum will help you learn the most in-demand Gen AI tools and languages, including Python, Google Colab, BERT, VS Code, Vector Database (Chroma/Pinecone), Transformers, RAG (Retrieval Augmented Generation), and Quick Fine-Tuning Techniques. 


Certificate from JHU: Earn a certificate from Johns Hopkins University upon completion of the course. 


Continuing Education Units: Earn 10 Continuing Education Units (CEUs) upon program completion. 


Learning support: Get personalized assistance from a dedicated program manager and academic support through the GL community, project discussion forums, and peer groups.

What are the key outcomes of this Gen AI course?

By the end of this Applied Generative AI Program, you will be able to: 


  • Understand the theoretical foundations of Generative AI and its applications 
  • Apply Generative AI techniques to create text, image, and multimedia content 
  • Implement best practices to mitigate potential risks in Generative AI solutions 
  • Develop and train Generative models using contemporary Machine Learning frameworks. 
  • Evaluate the ethical implications of Generative AI 
  • Critically analyze the impact of Generative AI on various industries and society as a whole.

What is the duration of this Generative AI course with a certificate?

The duration of this Applied Gen AI program is 16 weeks.

What is the structure and format of this Generative Artificial Intelligence program?

The Applied Generative AI program is offered in a flexible online format that includes 


  • Recorded video lectures 
  • Interactive mentoring sessions, and 
  • 2 live masterclasses by JHU faculty

What topics are covered in the curriculum of this Generative AI course by JHU?

The topics in the curriculum of this Applied Generative AI program include:

  • Key Concepts of Generative AI
  • Large Language Models
  • Python Programming with Generative AI
  • Foundations of AI
  • Generative AI for Business Productivity
  • Natural Language Processing
  • Predictive Analytics, Neural Networks, and Deep Learning
  • Prompt Engineering
  • Classification, Content Generation, and Summarization with Generative AI
  • Designing Advanced Generative AI Workflows
  • Secure and Responsible Generative AI Solutions
  • Developing Agents with Langchain
  • Retrieval Augmented Generation (RAG) Search
  • Advanced RAG
  • Fine-Tuning and Customization of Generative AI

Is there any project included?

Yes, a project based on leveraging Generative AI models for business is included in the curriculum of the Applied Generative AI program. You will begin this project in Week 9, followed by a one-week break.

Will I receive any learning and Academic support in JHU’s Generative AI course?

Yes, the Applied Generative AI Program offers comprehensive learning support, including: 


  • Personalized assistance from a dedicated program manager to stay on track and manage your learning journey effectively. 
  • Academic support through the GL community, project discussion forum, and peer groups.

What is the expected weekly time commitment for this program?

The weekly commitment will be 8-10 hours per week.

Who will be teaching this course?

This course is taught by renowned academicians and leading AI experts with real-world experience in leading AI practices at Fortune 500 companies. Here are some of the faculty and industry mentors teaching this course:


Dr. Ian McCulloh

Faculty Leader in AI and Strategy, Johns Hopkins University

Dr. Pedro Rodriguez

Faculty Member, Johns Hopkins University

Dr. Iain Cruickshank

Faculty Member, Johns Hopkins University

Dr. Pavankumar Gurazada

Senior Faculty, Academics, Great Learning

Jeremy Samuelson

Principal Data Scientist & ML Engineer, Equifax

Bhaskarjit Sarmah

Head RQA AI Labs, BlackRock


Note: This is an indicative list and is subject to change based on the availability of faculty and mentors

Will I receive a Gen AI certification from Johns Hopkins University upon completing this program?

You will receive a Certificate of Completion from Johns Hopkins University upon successful completion of the program. This is a certificate and not a certification.

What are the rankings of JHU?

JHU is a world-renowned university, which is ranked #6 

National University Rankings (U.S. News & World Report, 2025) 

#13 Best Global University (U.S. News & World Report, 2024)

What is the role of Great Learning in this program?

The Applied Generative AI program at Johns Hopkins University is delivered in collaboration with Great Learning. Great Learning will help you in enhancing your understanding with GL Coach, an AI-powered learning assistant.

How does this course help in transitioning to GenAI roles?

This Applied Generative AI Program offers a practical, hands-on approach to mastering Generative AI. You will 


  • Learn from JHU faculty and industry leaders. 
  • Build real-world GenAI applications and workflows. 
  • Work on projects and case studies aligned with business needs. 
  • Gain expertise in tools like LLMs, RAG, and Python. 
  • Earn a certificate and 10 CEUs from Johns Hopkins University. 


Together, these elements equip you with the skills, portfolio, and credibility needed to confidently transition into GenAI roles across industries.

Admissions & Eligibility

Who is this program for?

This Applied Generative AI Program is designed for individuals who are looking to explore how Generative AI can address real-world business problems.


This program is for: 


  • Technology professionals 
  • Data professionals 
  • Technology Consultants and Technical Managers 
  • STEM (Science, Technology, Engineering, and Mathematics) Graduates

Can I pursue this program while working full-time?

Yes, definitely. The classes are held on weekends, which allows you to pursue this program while working full time.

What is the admission process for the Generative AI program?

The admissions for the program close once the required number of participants enroll. Apply early to secure your spot. Here are the steps for admissions: 


1. Fill application form 

2. Interview process 

3. Join program

Fee & Payment

What is the total fee for the program?

The total fee for the Applied Generative AI Program is USD 2950.

Are payment plans or financing options available?

Yes, flexible EMI options and financial assistance may be available to eligible candidates. Please check with the admissions team during your application process.

Does the fee include Generative AI certification and all learning materials?

The program fee includes access to all course materials, live masterclasses, mentorship, and from Johns Hopkins University.

Others

What are CEUs, and how are they useful?

CEUs, or Continuing Education Units, are a recognized measure of participation in professional programs. Earning 10 CEUs from Johns Hopkins University demonstrates your commitment to formal learning and strengthens your credentials in the AI space.

How is Generative AI being used across industries?

Generative AI has become essential in almost every sector to automate processes, enhance customer experiences, streamline operations, and drive innovation. Here is how it is used in various sectors: 


  • Healthcare: Generating medical summaries, patient communication, and drug discovery insights. 
  • Finance: Automating reporting, fraud detection, and personalized financial advice. 
  • Marketing: Creating ad copy, product descriptions, and targeted campaigns. 
  • Technology: Powering AI copilots, code generation, and virtual assistants. 
  • Retail & E-commerce: Enabling personalized recommendations and chatbot support. 
  • Media & Entertainment: Generating scripts, music, visual assets, and game narratives.

What roles can I pursue after completing this Gen AI program?

After completing the Applied Generative AI Program, you will be prepared to pursue roles such as: 


  • Generative AI Engineer 
  • LLM Developer / Specialist 
  • Applied AI Scientist 
  • AI Product Manager 
  • Machine Learning Engineer 
  • AI Consultant or Innovation 
  • Lead Data Scientist 
  • AI Research Scientist 
  • Prompt Engineer 
  • NLP Engineer Robotics Engineer
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phone icon Application Closes 28th Aug 2025

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Get in touch with a Program Advisor from Great Learning & get your queries clarified.

Speak with our expert +1 410 584 3973 or email to office-appl-genai-gl@jhu.edu

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In collaboration with

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Johns Hopkins University is collaborating with online education provider Great Learning to offer the Certificate Program in Applied Generative AI. Great Learning is a professional learning company with a global footprint in 170+ 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.