Complement your Penn Engineering degrees with an Online Graduate Certificate in a rapidly expanding field. Our certificates in Data Science and Software Systems will give you the opportunity to dive deeper into critical areas of computer science. These for-credit credentials for Penn Engineering degree program alumni will give you a distinct advantage when seeking growth in your career.
The Data Science track combines the fundamentals of linear algebra and optimization with coursework in artificial intelligence, big data, computer vision, and more. If you choose Software Systems, you’ll study topics such as wireless communications, network security, blockchains, and cryptography. Whichever track you choose, you’ll specialize in a growing sector and maximize your career outcomes.
The Online Graduate Certificate from Penn Engineering Online is a for-credit credential that will produce an academic transcript and paper certificate. To earn a certificate, students can take a maximum of four (4) courses. Two of these four courses may be double-counted from your Penn Engineering graduate degree program.
Students may earn a maximum of two certificates. No course may be triple counted, i.e., counted for more than two credentials.
While most individuals will complete the Online Graduate Certificate program within one year, students may choose to extend their studies. In this case, all Certificate requirements must be met within a maximum of two years.
There are hardly any machine learning problems whose solutions do not make use of linear algebra. This course places emphasis on linear regression, data compression, support vector machines and more, which will provide a basis for further study in machine learning, computer vision, and data science.
View Full Course DescriptionThis course investigates algorithms to implement resource-limited knowledge-based agents which sense and act in the world. Topics include: search, machine learning, probabilistic reasoning, natural language processing, knowledge representation and logic. After a brief introduction to the language, programming assignments will be in Python.
View Full Course DescriptionThis course provides an overview of the field of natural language processing. The goal of the field is to build technologies that will allow machines to understand human languages. Applications include machine translation, automatic summarization, question answering systems, and dialog systems. NLP is used in technologies like Amazon Alexa and Google Translate.
View Full Course DescriptionThis course focuses on the fundamentals of scaling computation to handle common data analytics tasks. You will learn about basic tasks in collecting, wrangling, and structuring data; programming models for performing certain kinds of computation in a scalable way across many compute nodes; common approaches to converting algorithms to such programming models; standard toolkits for data analysis consisting of a wide variety of primitives; and popular distributed frameworks for analytics tasks such as filtering, graph analysis, clustering, and classification.
View Full Course DescriptionStructured information is the lifeblood of commerce, government, and science today. This course provides an introduction to the broad field of information management systems, covering a range of topics relating to structured data, from data modeling to logical foundations and popular languages, to system implementations.
View Full Course DescriptionThis is an introductory course to computer vision and computational photography. This course will explore four topics: 1) image feature detection, 2) image morphing, 3) image stitching, and 4) deep learning related to images. This course is intended to provide a hands-on experience with interesting things to do on images/pixels.
View Full Course DescriptionIn this course, students will learn a broad range of statistical and computational tools to analyze large datasets. This course provides a solid foundation of data science, statistics and machine learning to make data-driven predictions via statistical modeling and inference. Using case studies and hands-on exercises, the student will have the opportunity to practice and increase their data analysis skills using Python. The objective of these case studies is to identify and implement appropriate modeling and analysis techniques in order to extract meaningful information from large datasets.
View Full Course DescriptionThe course covers the methodological foundations of data science, emphasizing basic concepts in statistics and learning theory, but also modern methodologies. Learning of distributions and their parameters. Testing of multiple hypotheses. Linear and nonlinear regression and prediction. Classification. Uncertainty quantification. Model validation. Clustering. Dimensionality reduction. Probably approximately correct (PAC) learning. Such theoretical concepts are further complemented by exemplar applications, case studies (datasets), and programming exercises (in Python) drawn from electrical engineering, computer science, the life sciences, finance, and social networks.
View Full Course DescriptionThis course provides a rigorous and hands-on introduction to the field of software analysis – a body of powerful techniques and tools for analyzing modern software, with applications to systematically uncover insidious bugs, prevent security vulnerabilities, automate testing and debugging, and improve our confidence that software will behave as intended.
View Full Course DescriptionStudy today’s state-of-the-art wireless technology (4G LTE), next-generation wireless technology (5G NR), Wi-Fi technologies and the Internet of Things. You’ll build a simple IoT service with an IoT client device emulator and a real IoT server platform on the Internet.
View Full Course DescriptionThis is an introduction to topics in the security of computer systems and communication on networks of computers. The course covers four major areas: fundamentals of cryptography, security for communication protocols, security for operating systems and mobile programs, and security for electronic commerce.
View Full Course DescriptionThis course provides an introduction to fundamental concepts in the design and implementation of networked systems, their protocols, and applications. Topics to be covered include: Internet architecture, network applications, addressing, routing, transport protocols, peer-to-peer networks, software-defined networks, and distributed systems.
View Full Course DescriptionThis course focuses on the issues encountered in building Internet and Web systems, such as scalability, interoperability, consistency, replication, fault tolerance, and security. Examine how services like Google or Amazon handle billions of requests from all over the world each day, (almost) without failing or becoming unreachable. Study how to collect massive-scale data sets, how to process and extract useful information from them, and look at the massive, heavily distributed infrastructure that is used to run these services (and similar cloud-based services) today. This course will provide hands-on experience, using web search as our case study.
View Full Course DescriptionIntroducing the fundamentals of cryptography and distributed systems that underpin modern blockchain platforms — including collision-resistant hash functions, digital signatures and classical consensus algorithms and examining the architecture of modern blockchain platforms, and develop tools to analyze and interact with them in Python.
View Full Course Description*Note: Degree students will receive first priority for course registration.
Penn Engineering alumni are eligible to apply for Online Graduate Certificates. Current students may start the application for an Online Graduate Certificate during their last semester as a degree student and must graduate from their degree program before becoming an Online Graduate Certificate student. Below is a guide to show which Certificate students are eligible for based on their Penn Engineering major:
In order to register for an Online Graduate Certificate, Penn Engineering Online applicants will need to submit documentation through the application portal. The application consists of:
In one to two paragraphs, please:
Scan a copy of your official transcript or download a pdf from Path@Penn (Penn InTouch for Spring 2022 and earlier graduates).
Summer 2023 | Fall 2023 | Spring 2024 | |
---|---|---|---|
Application Form Opens | February 6, 2023 | May 1, 2023 | August 2, 2023 |
Application Form Closes | April 3, 2023 | July 5, 2023 | October 3, 2023 |
Decision Notification | April 6, 2023 | July 14, 2023 | November 10, 2023 |
Confirmation Form Due | April 24, 2023 | July 21, 2023 | December 7, 2023 |
Orientation Starts | April 26, 2023 | July 24, 2023 | December 2023 |
Classes Begin | May 8, 2023 | August 28, 2023 | January 2024 |
2022–2023 | Academic Year Costs* |
---|---|
Tuition | $3,200 per course unit |
Online Services Fees | $150 per course unit |
|
2023–2024 | Academic Year Costs* |
---|---|
Tuition | $3,330 per course unit |
Online Services Fees | $150 per course unit |
*Tuition and fees are posted as a guide and will be adjusted on a yearly basis. **Half Credit Courses are billed at half tuition and half fees. |
***Online Graduate Certificates are not eligible for federal financial aid.
Discover more about the Penn Engineering Online learning experience and what you can expect from virtual learning.
Online Graduate Certificate students will have access to the same resources as Penn Engineering Online degree students and continue their access to Penn Alumni services.
No, we cannot sponsor visas for students because these programs and courses are based entirely online.
Currently, only Penn Engineering degree program alumni are eligible to apply for the Online Graduate Certificates.
Current Penn Engineering students may begin the Graduate Certificate application process in the final term of their degree program.
Yes. However, students can never triple-count a course and only a maximum of four course units can be brought into MSE-DS for the Dual Degree. With this, you would still be completing six course units for the MSE-DS degree.