Drive Innovation with Applied GenAI Skills

Certificate Program in Applied Generative AI

Supercharge your career. Earn a Data Science certificate

16 week

Program Duration
Online

Mode of Learning
Weekly Live Sessions

With Industry Experts
10 CEUs

Johns Hopkins University

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Certificate Program in Applied Generative AI

Application closes 14^th Nov 2024

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Why choose the online Applied Generative AI course

Curriculum designed & delivered by JHU faculty
Monthly live online masterclasses by JHU faculty
Weekly live mentored learning sessions in small groups
Work on 2 Hands-on Projects and 6+ real-world case studies
Personalized assistance from a dedicated program manager
Certificate of Completion from Johns Hopkins University

Globally trusted by 9 million learners

National University Rankings

U.S. News & World Report
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.

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.

Comprehensive Curriculum

The curriculum, designed by the faculty of JHU, Great Learning, and leading industry practitioners, is 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.

Pre-work

This module provides all the necessary tools for your learning journey and establishes a solid foundation in three essential domains: Python programming, introduction to AI and its applications, and Statistics.

Module-01: Learning Python with Generative AI

This module provides a comprehensive introduction to Python programming fundamentals, focusing on Generative AI, and offers a solid understanding of how Large Language Models work.

Week-01: Generative AI Landscape

This week, you will learn 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/functions like Marketing, Healthcare and Productivity.

Week-02: Python Programming with Generative AI - 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, creation of a code, interpretation, debugging, etc

Week-03: 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, and also learn how to build ML classifiers using Gen AI and evaluate various machine learning models using Generative AI.

Week-04: Python Programming with Generative AI - 2

This week, you will learn how to interact with Generative AI using AI and libraries, and show how to interface and use different types of text and data modalities in Python. Building on top of the last week, you will learn how to use generative AI to be able to store text and work with text, able to read a file, able to manipulate and clean text data into python.

Module-02: Generative AI for Business Productivity

This module offers an opportunity to learn how to solve a variety of business problems using Generative AI. You will explore techniques such as text summarization, text classification, and text generation through prompting or Prompt Engineering with LLMs.

Week-05: Natural Language Processing And Image Classification

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

Week-06: Transformers for Large Language Models

This week, you will learn the foundational concept behind how Large Language Models (LLMs) work, specifically focusing on ‘self-attention’. Additionally, you'll 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-07: Prompt Engineering

This week, you will delve into 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'll discover how to build useful workflows to automate problem-solving with LLMs using LangChain.

Week-08: 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'll learn how to assess the quality of these solutions using objective metrics and other LLMs.

Week-09: Project-1 (Sample Business Problem)

Develop 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-03: 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 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 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 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’ll 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)

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

In-demand tools and libraries

Python
Google Colab
BERT
Vector Database (Chroma / Pinecone)
RAG (Retreival Augmented Generation)
Quick Fine-Tuning Techniques
VS Code
Transformers

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 hands-on projects and case studies

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

Mobile Technology, AI/ML Application Design

Python-based Application for Secure Data Storage

Objective: To design and develop a Python-based AI application for secure password generation and encrypted key storage using Generative AI models.

Skills Used: Python programming, AI/ML integration, data encryption, application development

Productivity Tools, Generative AI in Business

AI-Powered To-Do List Application with Summarization

Objective: To develop a Python-based AI application that helps users manage tasks, calendars, and notes through text summarization and advanced text manipulation.

Skills Used: Python programming, text manipulation, summarization, Generative AI integration

Productivity and Workflow Automation

AI-Powered Email Management Secretary

Objective: Develop 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.

Skills Used: Natural Language Processing (NLP), Machine Learning (ML), Summarization, Text Classification, Email Thread Management, API Integration, Python Programming, Prompt Engineering, Generative AI Applications

Business Operations, Generative AI in Automation

Generative AI-powered Meeting Notes Summarizer

Objective: To develop an AI-powered application that generates meeting notes summaries and enhances HR training through automated quiz generation using LLMs.

Skills Used: LLM development, prompt engineering, workflow automation

Note: This is an indicative list of projects & case studies 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.

* Image for illustration only. Certificate subject to change.

Best Global University

U.S. News & World Report
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

Program Fee

Program Fees: 2,950 USD

Apply Now

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.

1. Fill application form

Apply by filling a simple online application form.
2. Interview Process

Go through a screening call with the Admission Director’s office.
3. Join program

Selected candidates will receive an offer letter. Secure your seat by paying the admission fee.