Experts Say the 'New Normal' in 2025 Will Be Far More Tech-Driven, Presenting More Big Challenges

Artificial Intelligence And Machine Learning

Self-driving cars, intelligent assistants, and smart-home devices—we work to improve and discover AI technology in the fields of energy, finance, health care, education, transportation and more. We develop interactive decision-making tools, and create algorithms to respond to interdisciplinary fields where uncertainty is present: from construction management to the Mars rover. We investigate complex issues surrounding student persistence, and dig deep into machine learning.

"Students take a construction plan and overlay it with events that cause delays. Then we ask students to react to the scenarios."Nilufer Onder, associate professor, computer science, on developing ICDMA (interactive construction decision-making aid)

Current Project

Project Title: Revolution through Evolution: A Controls Approach to Improve How Society Interacts with Electricity

Investigators: Laura Brown

Sponsors: National Science Foundation

Overview: This CRISP (Computer Retrieval of Information on Scientific Projects) project addresses the challenges associated with the rapid evolution of the electricity grid to a highly distributed infrastructure. The keystone of this research is the transformation of power distribution feeders, from relatively passive channels for delivering electricity to customers, to distribution microgrids, entities that actively manage local production, storage and use of electricity, with participation from individual customers. Distribution microgrids combine the advantages of the traditional electricity grid with the advantages of emerging distributed technologies, including the ability to produce and use power locally in the event of grid outages. The project will result in a unified model that incorporates key aspects of power generation and delivery, information flow, market design and human behavior. The model predictions can be used by policymakers to guide a transition to clean energy via distribution microgrids. The expectation is to enable at least 50% of electric power to come from renewable resources. This cannot be done with either the traditional grid, due to its limited capacity to accommodate intermittent renewable power sources, or with fully decentralized approaches, which would not be affordable for most utility customers.

Researchers

Associate Professor, Computer Science

Associate Dean, Data Science Initiatives, College of Computing

Director, Data Science, M.S. And B.S. Programs

Area of Expertise

Artificial Intelligence and Machine Learning

Data Mining and Data Science

Applications of AI and ML to Energy (microgrids, power systems), Health, and other domains

Director, Great Lakes Research Center

Director, Institute of Computing and Cybersystems

William and Gloria Jackson Professor

Areas of Interest

Artificial Intelligence

Machine Learning

Signal and Image Processing

Sensor and Data Fusion

Heterogeneous Data Mining

Associate Professor, Computer Science

Associate Chair, Computer Science

Undergraduate Program Director, Computer Science

Area of Expertise

Artificial Intelligence

Automated Planning and Scheduling

Computer Science Education

Student Persistence in STEM

Dave House Associate Professor

Area of Expertise

Human-Computer Interaction (HCI)

Accessible computing

Speech and Language Processing

Mobile Interfaces

Crowdsourcing

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Graduate Certificate In Applied Artificial Intelligence And Machine Learning For Data Science

Who is the Applied AI/ML for Data Science Certificate for?

Drexel College of Computing & Informatics' Post-Baccalaureate/Graduate Certificate in Applied Artificial Intelligence & Machine Learning for Data Science provides the quantitative foundations, data analysis and interpretation, artificial intelligence (AI), machine learning (ML), and deep learning necessary for in-demand positions in Data Science and AI/ML. It focuses on the intersection of artificial intelligence & machine learning and data science, where applications of predictive modeling can help make sense of enormous amounts of data. 

This certificate can be combined with another certificate and courses to create Master of Science degrees as listed below.

Fast Facts

Number of Courses

5 (15 quarter credits)

Credits/full certificate can be applied to what master's degrees?

MS Artificial Intelligence & Machine Learning; MS Computer Science; MS Data Science

Time-to-completion

1 year

Format

On campus or online

Time Commitment

Full-time or part-time

Aid eligible

No

Tech experience required?

No

GRE required?

Recommended for international students and domestic students with a GPA lower than 3.0

Curriculum

IMPORTANT NOTE: Drexel operates on the quarter, not semester, system, offering classes during four 10-week terms throughout the year. 

This five-course program provides the quantitative foundations of AI/ML for Data Science, including data analysis and interpretation, machine learning, artificial intelligence, deep learning, and other related electives.

Please visit Drexel's Course Catalog for a full description of each required course and elective for this program. You can also find a sample Plan of Study for the certificate.

Admissions

A completed application for the online format or on-campus format.

A four-year bachelor's degree from a regionally accredited institution in the United States or an equivalent international institution.

A GPA of 3.0 or higher, in a completed degree program, bachelor's degree or above.

Official final transcripts from ALL Colleges/Universities attended. Please note: For students who have attended an institution outside of the US, it is highly recommended to submit a NACES approved course-by-course transcript evaluation (i.E., WES) for expedited review of your application. This approved evaluation will take the place of the transcript requirement to complete your application.

Graduate Record Examination (GRE) Scores (must be five years old or less) are not required but recommended for international students and domestic students below a 3.0 GPA. 

One letter of recommendation required, two recommended (academic, professional, or both).

Essay/Statement of Purpose (approximately 500 words).

Current Resume.

Pre-requisites for all graduate level programs: computer requirements and skills.

Additional requirements for International Students.

Please visit our Graduate Admissions section for application deadlines.

Request More Information

Be in touch with us to get answers to all your questions! We can connect you with a Recruitment Specialist, one of our Graduate Dean's Ambassadors, or a faculty member to help. Contact our recruitment team at cciinfo@drexel.Edu and we'll get back to you soon.

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