Applications for the MCIT Online Spring 2021 cohort are open. Register to attend an admissions webinar here.
The MCIT Online degree program requires the completion of 10 fully online computer science courses made up of six core courses and four electives. There are no required real-time sessions.
Introduction to Software Development (CIT 591) 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.
Mathematical Foundations of Computer Science (CIT 592) This course introduces students to math concepts that form the backbone of the majority of computer science. Topics covered include sets, functions, permutations and combinations, discrete probability, expectation, mathematical induction, and graph theory. The course goal of is to ensure students are comfortable with the math required for most CIS electives.
Introduction to Computer Systems (CIT 593) This course provides an introduction to fundamental concepts of computer systems and computer architecture. Students learn C programming language and an instruction set (machine language) as basis for understanding how computers represent data, process information, and execute programs.
Data Structures & Software Design (CIT 594) This course focuses on data structures, software design, and advanced Java; starting with an introduction to data structures and basics of algorithm analysis. Important data structures covered include arrays, lists, stacks, queues, trees, hash maps, and graphs. The course also focuses on software design and advanced Java topics such as software architectures, design patterns, and concurrency.
Computer Systems Programming (CIT 595) This course is a continuation of CIT 593 and introduces students to fundamental concepts in computing systems. Divided into two parts, the first half of the course introduces important concepts in modern operating systems: processes, scheduling, caching, and virtual memory. The second half of the course provides an introduction to fundamental concepts in the design and implementation of networked systems, their protocols, and applications. The course will use the C program language, and will develop your knowledge on C system calls, and libraries for process/thread creation and manipulation, synchronization, and network communication.
It is recommended that students take the core courses in sequential order. That said, students do not need special permission to take courses out of sequence so long as prerequisites and corequisites are followed. Note that new students must take CIT 591 in their first semester and students must complete four of the core courses before registering for electives.
MCIT Online students must complete four graduate-level electives. MCIT Online is still in the process of developing new electives. Additional elective courses planned for development include: Artificial Intelligence, Blockchain and more.
Descriptions of each course are on the MCIT Online Course List.
Courses are offered in the spring (January to May), summer (May to August), and fall (August to December), and the summer semester is optional. New cohorts start in fall and spring semesters. View a few sample course plans here.
Students may enroll in the MCIT Online program on a part-time or full-time basis. Students are allowed a maximum of seven years to complete the MCIT Online degree program.
Get familiar with online learning by taking Penn Engineering’s stand-alone course, Computational Thinking for Problem Solving, and assess your ability to think like a computer scientist. The course is open for enrollment and costs $49.
Take this quiz from Penn Engineering to help decide if now is the right time for you to pursue this degree. Note: This quiz will in no way factor into your application -- this is purely to assess your ability to thrive in an online degree program and to help you prepare for success in MCIT Online. This blog post helps explain more about the expectations of the degree.
|Sample Schedule||MCIT Online Sample 2 Year Plan||Tuition + Fees||MCIT Online Sample 3.5 Year Plan||Tuition + Fees|
|Fall||CIT 591 - Intro to Software Development + CIT 592 - Mathematical Foundations of Computer Science||$5,272||CIT 591 - Intro to Software Development||$2,636|
|Spring||CIT 593 - Intro to Computer Systems + CIT 594 - Data Structures & Software Design||$5,272||CIT 592 - Mathematical Foundations of Computer Science||$2,636|
|Summer||CIT 595 - Computer Systems Programming||$2,636||CIT 593 - Intro to Computer Systems||$2,636|
|Fall||CIT 596 - Algorithms & Computation + Elective||$5,272||CIT 594 - Data Structures & Software Design||$2,636|
|Spring||Elective+ Elective||$5,272||CIT 595 - Computer Systems Programming||$2,636|
|Summer||Elective||$2,636||CIT 596 - Algorithms & Computation||$2,636|
Students can access all course materials wherever and whenever with the mobile app, used by over 80 percent of degree students on Coursera. The app is available on iOS and Android.
Using the mobile app, learners can:
Coursera does not grant credit, and does not represent that any institution other than the degree granting institution will recognize the credit or credential awarded by the institution; the decision to grant, accept, or transfer credit is subject to the sole and absolute discretion of an educational institution.
We encourage you to investigate whether this degree meets your academic and/or professional needs before applying.
Penn Engineering offers an online Computational Thinking for Problem Solving course on Coursera to help you decide whether the program is the right fit before you apply.