First Year Experience

Welcome to FYE!  If this is your first time with us, we recommend that you start out by reading our Getting Started page, then clicking through each of the navigation links on the left side of this website.  Check back often because this site is continuously updated!

In general, FYE is the home for three foundational computing courses:

  • CSE 1300 - Introduction to Computing Principles.  This is a good course for those who are new to computing and does a great job for prepping you to take CSE 1321.  You'll learn about a variety of computing concepts and do some programming as well.  For many students, this can count as an elective, so ask your advisor about it.
  • CSE 1321 - Programming and Problem Solving I.  This is where you'll learn the foundations of programming.  It focuses on problem solving and has a lab component - CSE 1321L - where you'll apply those problem-solving skills using Python.
  • CSE 1322 - Programming and Problem Solving II.  This class extends what you learned in CSE 1321 and also has a lab component - CSE 1322L (Java and C# labs are available).

The FYE is a group of people dedicated to helping you become a successful computing professional. Our team includes Lecturers, Graduate Teaching Assistants, Graduate Research Assistants, Graders, and Tutors who are all here to help you do your very best.  

We're all here to help, so when you get stuck, make sure you ask for help!   Our office is in the J/Atrium building on the 3rd floor, room J3114.   We're also available through email. 

Again, welcome to FYE.  We’re excited to be here, and we’re looking forward to making your first year of computing the best year ever.

The FYE Team

Getting Started

Welcome to CCSE's First-Year Experience (FYE)!  If you're reading this, you're probably either in CSE 1101, CSE 1321 or CSE 1322.  This page is here to get you started and is intentionally minimalistic.  The FYE website serves as a central repository for just about everything in this course, so make sure you explore it thoroughly!

    • For online courses, you should be able to log into D2L.  Go ahead and log in.
    • Buy a webcam if you do not already have one equipped on your computer or laptop.
    • The expected workload of these courses is between 6-10 hours per week for a 16-week period.  For summer courses, you can expect to double that.  Make sure you have (scheduled) time to complete the course.
    • Find a backup Internet connection - which is critical for exam days!  Some set up their phone as a "hotspot" while others hit the local coffee shop.  You only have 2 hours for an exam, so think about this ahead of time.
    • You have a different lecture professor and lab instructor.  Find out who both of them are and what their contact information is - which should be found in D2L.
    • Install an IDE (Integrated Development Environment) Right now, we're using PyCharm for Python, Visual Studio for C# arnd IntelliJ for Java.
    • Explore this website - and pay special attention to the Resources page.  Understand that we have tutoring, office hours, advising and so on.  We also have additional help there.
    • Read the syllabus and look at our Academic Policies.  We have a really interesting Final Exam policy that you might like.
    • Get familiar with the tech.
      • Gradescope is how you'll submit your assignments and labs.  We'll automatically add you, you don't have to do anything.
      • D2L is what we use as the "shell" for the course.  You should be able to log into that if you're enrolled in the class.  You should see a syllabus quiz there, so complete that.
      • Online exams use Respondus and Lockdown Browser, so watch this 2-minute video.
    • Practice coding; you'll start to see patterns. Becoming a good programmer is like becoming a good piano player.  You can't just watch a teacher play, you have to play the instrument yourself.  Practice builds confidence for exams as well.
    • Check your email.  We send you things and you need to know about them.
    • Start assignments early.  Assignments are easier at the beginning of the semester than the end of the semester -  becoming progressively harder.  You'll have a higher shot at success if you start early.
    • Ask questions.  If you get stuck, ask questions.  A rule of thumb is if you can't make even small progress in about 30-45 minutes, you should ask for help.
    • Don't cheat. If things go well, you're going to graduate in 4 or 5 years.  Chances are high that you'll have a technical job interview where they ask you to write code.  If you didn't learn what you needed to in these classes, this will be a highly embarrassing time for you.  We want you to get that high-paying job!
    • Learn all you can and master the content to the point you can teach others.  If you know the content and can teach others, consider becoming a Teaching Assistant (TA) here in the College of Computing and Software Engineering!

FYE Learning Outcomes by Course

  • This course provides a survey of computing. Particular topics include Problem Solving, Computational Thinking, Hardware, Operating Systems, Cloud Computing, Cybersecurity, Artificial Intelligence, Data Analysis, Web Development, and provides an introduction to programming in Python. A companion hands-on lab, CSE 1101L, is available and may be taken independently for students seeking applied experience.

    Students who successfully complete this course will be able to:

    • Demonstrate an understanding of how computers work, including an overview of hardware, logic gates, binary, and operating systems.
    • Demonstrate an understanding of cloud computing, cyber security principles, basic networking.
    • Demonstrate an understanding of Data Analysis using spreadsheets, databases and data visualization.
    • Demonstrate an understanding of the basics of programming.
    • Use computational thinking to ask questions and find different ways to solve problems.

  • This lab course will allow students to explore various computing fields in real world scenarios. Topics may include Problem-solving, Computational Thinking, Hardware, Operating Systems, Cloud Computing, Cybersecurity, Artificial Intelligence, Data Analysis, Web Development, and provides an introduction to programming in Python. This hands-on lab complements CSE 1101 lecture but may be taken independently; students who wish to gain a broader understanding of computing concepts are encouraged to also take the lecture.

    Students who successfully complete this course will be able to:

    • Demonstrate an understanding of how computers work, including a overview of hardware, logic gates, binary, and operating systems.
    • Demonstrate an understanding of cloud computing, cyber security principles, basic networking.
    • Demonstrate an understanding of Data Analysis using spreadsheets, databases and data visualization.
    • Demonstrate an understanding of the basics of programming.
    • Use computational thinking to ask questions and find different ways to solve problems.

  • This course provides an introduction to computing with a focus on programming. Instruction centers on an overview of programming, problem-solving, and algorithm development. Particular topics include object-oriented design/programming, primitive data types, arithmetic and logical operators, selection and repetition structures, interactive user input, exception handling, using and designing basic classes, single-dimensional data structures with searching and sorting, and arrays. Programming assignments focus on techniques of good programming style including proper documentation. The student is taught to efficiently design, code, and debug problem solutions and the relationship between correct code and security.

    Students who successfully complete this course will be able to:

    • Apply computational methods to analyze data and solve real-world problems.
    • Demonstrate the appropriate use of data types and logical, relational, and arithmetic expressions in programs.
    • Construct algorithmic solutions that incorporate selection and repetition.
    • Implement collections appropriately to store and analyze data.
    • Define functions and classes in program solutions.

  • Students who complete this course successfully will be able to:

    • Apply computational methods to analyze data and solve real-world problems.
    • Demonstrate knowledge of the syntax of a specific programming language.
    • Employ IDEs and compilers to learn how to compile, debug, run and test programs.
    • Demonstrate the appropriate use of data types and logical, relational, and arithmetic expressions in programs.
    • Construct algorithmic solutions that incorporate selection and repetition.
    • Implement collections appropriately to store and analyze data.
    • Define functions and classes in program solutions.

  • The second course in computing provides coverage of more advanced topics of object-oriented programming. This includes the use of static variables and classes, non-linear data structures, inheritance and polymorphism, file input/output, exception handling, recursion, and parameterized types. Elementary data structures (linked lists, stacks, and queues) are introduced to solve application problems. Graphical user interfaces, parallel programming, database programming, and event-driven programming are also introduced. Students will use good programming style including proper documentation.

    Students who complete this course successfully will be able to:

    • Demonstrate more advanced skills in programming, including the ability to handle multi- dimensional arrays
    • Demonstrate file handling techniques and exception code.
    • Recognize the difference between iterative and recursive approaches.
    • Demonstrate the ability to use linked lists, stacks, and queues in problem solving.
    • Compare "program driven" and "event-driven" approaches to user interaction, including the relationship between event-driven programs and Graphical User Interfaces
    • Discuss principles of concurrency and parallelism.

  • Students who complete this course successfully will be able to:

    • Demonstrate more advanced skills in programming, including the ability to handle multi-dimensional arrays
    • Design and use classes, including inherited classes
    • Demonstrate file handling techniques and exception code in a program
    • Recognize the difference between iterative and recursive approaches and use them correctly in a program
    • Demonstrate the ability to use linked lists, stacks, and queues in problem solutions
    • Understand "program driven" and "event-driven" approaches to user interaction, including the relationship between event-driven programs and Graphical User Interfaces
    • Apply computing concepts in the domains of parallelism and databases

Registering for CSE 1321/L and CSE 1322/L

Welcome to the registration portal for CSE 1321/L and CSE 1322/L courses at the College of Computing and Software Engineering (CCSE). We are thrilled to invite you to embark on a transformative academic journey that combines innovative learning with practical experiences. Get to know the essential information and step-by-step guidance you need to successfully register for these courses. Discover the exciting world of computer science, guided by expert faculty and a supportive learning environment.

registration