July 30, 2024

Lifelong Learning with Penn Engineering Online: MOOCs

Looking for ways to expand your knowledge of emerging technologies?  Maybe you’ve considered pursuing graduate studies in engineering; or perhaps you’re just interested in casually learning more about topics like computer programming, data analysis or machine learning. Regardless of your background or future goals, we invite you to explore our Lifelong Learning offerings and join us for a MOOC (Massive Online Open Course)

MOOCs are on-demand, noncredit courses that provide learners with an easy way to dip your toes into subjects like Python, Java, artificial intelligence or data analysis – without needing to commit to an entire degree program.

Each MOOC is fully self-paced, so you can study anytime from anywhere. Most courses can be completed in three to eight weeks, but you can work through the material at whatever speed accommodates your schedule and availability. You can enroll in a single course or can continue on to complete a designated series of courses and earn a Specialization Certificate in that subject.

Penn Engineering Online is committed to ensuring that these on-demand courses are open to everyone. MOOCs are priced affordably, ensuring that anyone who wants to enroll can do so accessibly.

With courses that explore a range of topics from Data Analysis Using Python to Deep Learning Essentials, our MOOCs provide a pathway into a variety of disciplines within engineering. No matter how much experience you have with technology, you will find a MOOC that can meet you where you are and help you take your skills and knowledge to the next level.

We offer cutting-edge courses in three categories: 

General Courses
Including Computational Thinking for Problem Solving and Urban Transit for Livable Cities

Programming
Including Introduction to Python Programming and Inheritance and Data Structures in Java

AI and Machine Learning
Including Artificial Intelligence Essentials and Statistics Essentials 

The courses that are best for you depend on your background in tech and your specific learning goals. For instance, if you’re considering applying to our online Master of Computer and Information Technology (MCIT Online) degree program and have no prior experience in programming, you might be interested in signing up for Computational Thinking for Problem Solving to get a feel for this subject matter and starting to think like a computer scientist. On the other hand, if you already have some exposure to the tech field and want to upskill by earning a new credential in one of today’s most in-demand areas of study, one of the courses in the AI and Maching Learning Essentials specialization could be a good choice. 

As a student in one of our MOOCs, you’ll learn from members of the renowned University of Pennsylvania’s faculty who have their fingers on the pulse of the latest industry research and developments. These are the same professors who lead courses for students who matriculate into Penn Engineering’s Ivy League degree programs. Here are just a few of the outstanding faculty members who you can study under in our MOOCs:

Chris Callison-Burch is a prominent researcher and subject-matter expert in the field of AI who has testified before Congress about the relationship between generative AI and copyright law. He has spent decades exploring his primary arenas of research including large language models. He teaches our Artificial Intelligence Essentials MOOC and is a Professor for the department of Computer and Information Science. Callison-Burch also teaches two of our Penn Engineering Online degree program courses:

CIS 5210 Artificial Intelligence

CIS 5210

Artificial Intelligence

This 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. This course must be taken in the first semester of the program.

Pre-Requisites

CIT 5910, CIT 5920, CIT 5940, and CIT 5960

CIS 5300 Natural Language Processing

CIS 5300

Natural Language Processing

This 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.

Pre-Requisites

CIT 5910 Introduction to Software Development, CIT 5920 Mathematical Foundations of Computer Science , and CIT 5940 Data Structures & Software Design. Recommended: CIT 5960

Susan Davidson is a data science pioneer and an award-winning scholar whose research has spanned domains from database technologies to innovations in biotechnology. Her primary research interests include database and web-based systems, scientific data management, provenance, crowdsourcing, and data citation. Her experience include serving as Founding Co-Director for the Center for Bioinformatics and both Founder and Chair for Advancing Women in Engineering. She currently serves as Co-Director of the on-campus MSE-DS degree program. She teaches our Computational Thinking for Problem Solving MOOC and is a Weiss Professor for the department of Computer and Information Science. Davidson also teaches one of our Penn Engineering Online degree program courses:

CIS 5500 Database & Information Systems

CIS 5500

Database & Information Systems

Structured 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. We will study the relational data model; SQL; database design using the Entity-Relationship model and relational design theory; transactions and updates; efficient storage of data; indexes; query execution and query optimization; and “big data” and NoSQL systems.

Pre-Requisites

CIT 5910 Introduction to Software Development, CIT 5920 Mathematical Foundations of Computer Science | Knowledge of Javascript & Web Development (HTML, CSS) is recommended. | Recommended Corequisite: CIT 5960 Algorithms & Computation

Brandon Krakowsky is the Director of Data Computing and Research Support for the Wharton AI and Analytics Initiative, which advances the exploration of cutting-edge technology and the development of analytics methods in modern business. He teaches all four MOOCs in the Introduction to Programming with Python and Java Specialization and is a Lecturer for the department of Computer and Information Science. Krakowsky also teaches two of our Penn Engineering Online degree program courses:

CIT 5910 Introduction to Software Development

CIT 5910

Introduction to Software Development

This course is an introduction to fundamental concepts of programming and computer science for students who have little or no experience in these areas. Includes an introduction to programming using Python, where students are introduced to core programming concepts like data structures, conditionals, loops, variables, and functions. Also provides an introduction to basic data science techniques using Python. The second half of this course is an introduction to object-oriented programming using Java, where students are introduced to polymorphism, inheritance, abstract classes, interfaces, and advanced data structures. Students will also learn how to read and write to files, connect to databases, and use regular expressions to parse text. This course includes substantial programming assignments in both Python and Java, and teaches techniques for test-driven development and debugging code.

Pre-Requisites

No Pre-Requisites

EAS 5740 How to Use Data (.5 CU)

EAS 5740

How to Use Data (.5 CU)

This 0.5 CU course is an excellent introduction for those who want to learn about the mechanics of data, performing data analysis to gain insights, applying data science techniques to make predictions, and applying data analytics to answer questions and to address interesting business problems. Students will learn how to interpret and frame business problems to be addressed by analytics. The course will also cover different elements of the data analytics process, including data wrangling and cleaning, data exploration and descriptive analytics, data modeling, machine learning, predictive analytics, data visualization and the presentation of analysis and insights using data storytelling. While we will touch upon essential theoretical and technical concepts, our primary focus in this course will be on the practical application of data skills.

WATCH COURSE PREVIEW HERE

Pre-Requisites

CIT 5910

Vijay Kumar serves as Nemrovsky Family Dean of the School of Engineering and Applied Science with appointments in the departments of Mechanical Engineering and Applied Mechanics, Computer and Information Science, and Electrical and Systems Engineering. Heis a fellow of ASME and IEEE and has been elected to the National Academy of Engineering, American Philosophical Society, and the American Academy of Arts and Sciences. He is also the founder of Exyn Technologies. He teaches the Robotics 1: Aerial Robotics MOOC in the Introduction to Robotics Specialization. 

If you’re looking to get more than a single-course experience, you can pursue a specialization and dive deeper into a particular topic of interest by taking a series of four to six related MOOCs that lead to a credential. Once you’ve completed all the courses designated within a specialization, you can earn a Specialization Certificate. We offer the following specializations:

While many online learning platforms merely record existing lectures from on-campus degree programs, Penn Engineering Online is committed to providing a much more thoughtfully produced and engaging student experience. Each of our MOOCs is carefully designed and developed in partnership with our dedicated Instructional Design Team, who also drive the creation of the robust for-credit courses in our Penn Engineering Online degree programs. Throughout each phase of the course development process, our Instructional Designers are committed to meeting the specific needs of online learners. They work closely with faculty to  ensure that students will enjoy an impactful, interactive learning experience.

While going through each MOOC, you’ll learn through a combination of lecture videos and other exercises such as assignments, readings, discussion prompts, quizzes or peer reviews. Many learners choose to enroll in one of our MOOCs as a way to try out this online learning environment before deciding to apply to one of our online master’s degree programs. Whether they are interested in the MSE-AI Online, MSE-DS Online or MCIT Online degree program, these open courses can be a great way for prospective students to get a feel for our style of course production and the asynchronous learning model as they decide whether a degree program is the right path for them to pursue. However, it is important to note that MOOCs DO NOT embody the same level of rigor as the courses in our degree programs. MOOCs should not be used to assess the time commitment, academic challenge or rate of learning that a student could expect from a Penn Engineering Online master’s degree program.

Whether you choose to enroll in an individual MOOC or complete a full Specialization Certificate, these convenient, high-caliber credentials will expand your knowledge and allow you to gain an edge in the workplace. It’s never been easier to access an Ivy League academic experience, acquire relevant new skills and advance your career in new directions. If you are ready to start learning, browse our course offerings and enroll today!