Elevate Your Career with AI Skills
Certificate Program in Applied AI
Application closes on
21st Aug 2025
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Certificate Program in Applied AI
Application closes 21st Aug 2025
Why Applied AI?
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AI is reshaping how businesses operate
AI is driving structural changes across functions. Organizations are scaling AI to unlock value.
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Build the most in-demand skill today
AI isn’t replacing jobs; people who use AI are. Stay relevant and future-proof your career.
APPLY AI TO SOLVE BUSINESS CHALLENGES
Elevate your skills in Applied AI
Learn techniques to extract actionable insights and solve complex business challenges
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Understand core AI concepts, identify problems, and associated ethical implications.
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Apply key Python libraries to prepare data for analysis and modeling.
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Analyze data to effectively communicate business insights across industry scenarios.
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Implement and evaluate supervised learning algorithms and anomaly detection techniques.
Earn a Certificate of Completion from Johns Hopkins University
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#6 National University Rankings
U.S. News & World Report, 2025
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#1 Computer Information Technology
U.S. News & World Report, 2025
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#13 Best Global University
U.S. News & World Report, 2024
Key program highlights
Why choose the Applied AI program
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Learn from a top-ranked university
Learn from expert JHU faculty and industry leaders.
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Industry-aligned curriculum
Learn the foundations of Python, GenAI, and Deep Learning, gain valuable insights, and apply your skills to transition into AI roles.
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Hands-on learning
Drive business value strategically using AI through hands-on labs, projects, and real-world case studies.
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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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AI-assisted learning
AI-powered tools support learning content and practice activities to enhance learning efficiency and engagement.
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Dedicated support
Access a dedicated Program Manager and Academic Learning Support, which includes discussion forums and peer groups.
Skills you will learn
Visual Content Generation
Statistical Analysis
Natural Language Processing
Prompt Engineering
Retrieval-Augmented Generation (RAG)
AI Agents & Workflows
LLM Workflows
Visual Content Generation
Statistical Analysis
Natural Language Processing
Prompt Engineering
Retrieval-Augmented Generation (RAG)
AI Agents & Workflows
LLM Workflows
Advance your career with Artificial Intelligence
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AI top 3 priority
For 75% companies
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GenAI Job Surge
411% rise in roles
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AI Skills Pay
56% premium wages
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Up to $ 150K
avg annual salary
Careers in Artificial Intelligence:
Roles you can unlock with Applied AI skills
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Applied AI Specialist
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AI Analyst
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Machine Learning Engineer
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AI Solutions Associate
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NLP Engineer
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AI Product Manager
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AI Strategy Consultant
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Prompt Engineer
Our alumni work at top companies
- Learning Journey
- Curriculum
- Projects
- Tools
- Certificate
- Faculty
- Mentors
- Career support
- Fees
This program is ideal for
Working professionals at various stages of their careers who are looking to advance their knowledge and skills in AI.
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STEM graduates
Looking to secure their first role in the data and AI industry, with a focus on building a strong foundation of technical skills and practical experience.
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Early to mid-career
Professionals seeking to transition into AI roles by acquiring the skills and knowledge necessary to navigate and excel in this fast-evolving field.
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Senior professionals
Senior Professionals looking to upskill in AI to stay ahead in their careers by deepening their understanding of advanced AI concepts and applications relevant to their industry.
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Tech leaders
Who want to leverage AI for strategic planning, innovation, and data-driven business decision-making.
PROGRAM CURRICULUM
The curriculum is designed by the faculty of Johns Hopkins University and leading industry practitioners. It is taught by best-in-class professors, practicing industry experts, and professionals from leading global companies.
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Self-paced
Modules
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Live
Faculty-led masterclasses
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Live
Expert mentorship sessions
PRE-WORK
This module will help learners navigate the AI landscape by identifying key problems and solution spaces, enabling businesses to leverage AI technologies effectively, acquire fundamental programming skills in Python to build the necessary foundation to develop AI solutions to support business initiatives, and apply foundational concepts of probability and statistics as a foundation to analyze data and inform strategic decision-making.
- AI Landscape - Problems and Solution Spaces
- Introduction to Python
- Fundamentals of Probability and Statistics
MODULE 01: PYTHON FOR DATA-DRIVEN INSIGHTS
This module focuses on building a strong foundation in data analytics and applying the ROAD framework to identify and solve key business challenges using data-driven approaches. Learners will also utilize Python for data transformation and feature engineering to prepare datasets, and conduct exploratory and statistical analysis to uncover trends and patterns in data, enabling informed business decisions and strategic planning.
- Introduction to Data Analytics
- Python Fundamentals for AI
- Python for Data Transformation and Feature Engineering
- Exploratory Analysis and Visualization
- Introduction to Statistical Analysis
- Learning Break
- Project 01
MODULE 02: APPLIED MACHINE LEARNING FOR PREDICTIVE ANALYTICS
This module focuses on building a strong foundation in core machine learning techniques by exploring supervised and unsupervised learning approaches and their real-world applications. It enables participants to model, classify, cluster, and detect patterns in data using algorithms such as linear regression, decision trees, K-means clustering, and anomaly detection techniques. Learners will also explore techniques for tuning and evaluating these models for optimizing predictive performance.
- Regression Techniques
- Classification Methods
- Clustering Algorithms
- Anomaly Detection
- Project 02
- Learning Break
MODULE 03: NEURAL NETWORKS AND COMPUTER VISION
This module builds a strong foundation in deep learning and modern AI by exploring neural network models. Learners will explore the fundamental concepts of neural networks and their application to classification tasks, examine the unique architecture of CNNs and their applications, such as object detection and facial recognition, understand the principles behind diffusion models, and how to generate high-quality images from textual descriptions.
- Neural Networks for Classification
- CNNs for Vision Applications
- Image Generation with Stable Diffusion
- Project 03
- Learning Break
MODULE 04: GENERATIVE AI FOR NLP
This module builds a strong foundation in NLP and Generative AI for text-based applications to enhance communication and create innovative solutions. Participants will implement prompt engineering and retrieval-augmented generation (RAG) techniques to improve response accuracy and relevance in AI-driven systems, and design and build agentic AI workflows that automate tasks and optimize processes.
- NLP and Generative AI for Text Analytics
- Retrieval-Augmented Generation for Contextualized Q&A
- Building Agentic AI Workflows
- Project 04
SELF PACED MODULES
The courses below are self-paced (released after the core learning journey).
MODEL DEPLOYMENT (LIVE MASTERCLASS ONLY)
This module lays the foundation for model deployment, enabling the realization of an AI model's value and the development and deployment of web applications using Python.
- Introduction to Model Deployment
- Web App Deployment
REINFORCEMENT LEARNING
This module lays a foundation in the fundamental principles and components of reinforcement learning (RL), explores the working mechanisms of its various components, and covers techniques such as Q-learning and SARSA algorithms.
- Reinforcement Learning Framework
- Q-Learning
- SARSA Algorithm
RECOMMENDER SYSTEMS
This module introduces recommendation systems, focusing on building personalized models that leverage historical product purchase and satisfaction data to generate high-quality recommendations tailored to individual user preferences.
- Introduction to Recommender Systems
- Market Basket Analysis
- Collaborative Filtering
- SVD Approach
- Hybrid Recommender Systems
DIMENSIONALITY REDUCTION
This module builds a foundation in Dimensionality Reduction techniques, essential for simplifying complex datasets while preserving their intrinsic structures, covering Principal Component Analysis (PCA) and t-distributed Stochastic Neighbor Embedding (t-SNE) to transform high-dimensional data into lower-dimensional representations for visualization and storage.
- Introduction to Dimensionality
- Reduction Principal Component Analysis (PCA)
- t-distributed Stochastic Neighbor Embedding (t-SNE)
Work on hands-on projects and case studies
Gain practical, hands-on skills and leverage AI to solve business challenges.
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Hands-on
projects
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Real-world
case studies
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Industry relevant
tools and techniques
RETAIL, E-COMMERCE
Retail Order Query Chatbot
Description
Learn how to create an AI-powered chatbot using prompt engineering and large language models to improve customer service and help with order tracking in e-commerce.
Skills you will learn
- Large Language Models
- Prompt Engineering
- AI Agents
- Context-Aware Chatbots
- Order Tracking Automation
- Python
E-COMMERCE, DIGITAL MARKETING
Measuring What Drives Online Purchase Decisions
Description
Explore how to use statistical methods to discover what influences online purchase decisions, helping improve marketing campaigns and boost conversions.
Skills you will learn
- Statistical Analysis
- Statistical Testing
- Data-Driven Decision Making
- Python
HEALTHCARE, MEDICAL ANALYTICS
Predicting Cardiovascular Disease Risk
Description
Learn how to build a classification model using patient health data to assess the risk of heart disease and help improve preventive care.
Skills you will learn
- Decision Trees
- Ensemble Learning
- Random Forests
- Model Tuning
- Model Evaluation
- Classification
- Python
MARKETING, CREATIVE TECHNOLOGY
AI-Powered Visual Content Generation System
Description
Explore how to build an AI solution that generates personalized images from text to support creative campaigns for brands and NGOs.
Skills you will learn
- Generative AI
- Visual Content Generation
- Prompt Engineering
- Image Generation
- Stable Diffusion
- Python
Master in-demand AI & ML tools
Gain hands-on experience with 20+ tools and techniques
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Python
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Pandas
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NumPy
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Scikit-Learn
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ChatGPT API
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Hugging Face
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Llama Cpp
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ChatGPT
And More...
Earn a certificate of completion from Johns Hopkins University
Get Continuing Education Units (CEUs) and a globally recognized credential from a top U.S. university and showcase it to your network.
* Image for illustration only. Certificate subject to change.
Meet your faculty
Learn from renowned Johns Hopkins University faculty with expertise across AI, machine learning, and applied analytics.
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Dr. Anthony (Tony) Johnson
Senior Professional Staff Member and Research Scientist, Applied Physics Laboratory, Whiting School of Engineering, Johns Hopkins University
Former AI researcher at HEC Montréal specializing in deep learning
Expert in NLP, computer vision, and meta-learning for real-world AI tasks
Know More
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Dr. Ian McCulloh
Manager, AI Continuing and Exec Ed, Johns Hopkins University
Served as Chief Data Scientist and MD of AI at Accenture Federal Services
Author of three books and over 100 peer-reviewed papers
Know More
.jpg "Dr. Anthony (Tony) Johnson - Faculty Director")
LinkedIn Profile
University LinkInteract with our mentors
Interact with dedicated and experienced AI experts who will guide you through your learning journey
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Prabhat Bhattarai
Data Scientist Apple
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Priyanka Singhal
Assistant Vice President (AI Research), US Bank
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Vinicio Desola Jr
Senior AI Engineer Newmark
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Pankaj Kumar
Data Science Manager Republic Finance
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Sundeep Pothula
Product Data Scientist Moveworks
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Marcelo Guarido de Andrade
Research Assistant at University of Calgary University of Calgary
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Omid Badretale
Senior Research Data Scientist | Alternative Data RBC Capital Markets
Get your dream job with dedicated career support
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1:1 career sessions
Interact personally with industry professionals through career mentoring sessions to get valuable insights and guidance
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Interview preparation
Gain insider insights into what recruiters look for. Access curated career prep material and practice with unlimited AI-powered mock interviews.
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Resume & profile review
Polish your resume using an AI-assisted builder to better showcase your skills and experience.
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E-portfolio
Build an industry-ready portfolio to showcase your mastery of skills and tools
Program fee
The course fee is 3,700 USD
Advance your career
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Understand core AI concepts, identify problems, and associated ethical implications
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Understand NLP, GenAI, and experiment with models like Transformers & Stable Diffusion
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Implement and evaluate RAG systems to enhance LLM performance through context
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Develop practical LLM workflows using prompt engineering, fine-tuning, and AI agents
Easy payment plans
Avail our EMI options & get financial assistance
Third Party Credit Facilitators
Check out different payment options with third party credit facility providers
*Subject to third party credit facility provider approval based on applicable regions & eligibility
Registration process
Our registrations close once the requisite number of participants enroll for the upcoming batch. Apply early to secure your seat.
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1. Fill application form
Register by completing the online application form.
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2. Application screening
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.
Batch start date
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Online · To be announced
Admissions Open
Application Closes
21st Aug 2025
Delivered in Collaboration with:
Johns Hopkins University is collaborating with online education provider Great Learning to offer the Certificate Program in Applied 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.
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