## DASC 5100 Programming Fundamentals (3 Credit Hours) ### Section A Fall 2025 Dr. Husam Ghazaleh [email protected] Lecture Meeting Time: Asynchronous Online Office Hours: MWF 11:00am–12:30pm, and by Appointment using Microsoft Bookings Office Location: Birck Hall 132 Telephone Number: 630-829-2171 Department Chair: Dr. Anthony DeLegge – Birck 125, [email protected] Course Description: Introduction to foundational programming concepts. The course is specif- ically designed for students without prior programming experience. Topics include syntax, condi- tionals, loops, functions, lists, strings and dictionaries. Data structures such as trees and heaps are also discussed. 3 semester credit hour/s. **Course Topics:** [[1. Introduction to Computers and Python|1. Introduction to Computers and Python]] [[2. Introduction to Python Programming|1. Introduction to Python Programming]] [[3. Control Statements and Program Development|3. Control Statements and Program Development]] [[4. Functions|4. Functions]] [[5. Lists and Tuples|5. Lists and Tuples]] [[6. Dictionaries and Sets|6. Dictionaries and Sets]] [[7. Strings|6. Strings]] TextBook: Deitel, P., & Deitel, H. M. (2020). Revel for Intro to Python for computer science and data science (brief version), 1st Edition. Pearson. Course Learning Outcomes General Education Goals and Outcomes G1. Critical Thinking and Problem-Solving G1.a. Demonstrate critical thinking and analysis G1.b. Identify, study, and solve problems G2. Personal Growth G2.a. Develop intellectual curiosity and a desire for lifelong learning G3. Breadth of Knowledge and Integrative Learning G3.a. Explore connections between classroom knowledge and real-world ex- periences 1 [](https://outlook.office.com/bookwithme/user/[email protected]/meetingtype/7NWcaFl__0q11k8ogFHZrA2?anonymous&ep=mcard "https://outlook.office.com/bookwithme/user/[email protected]/meetingtype/7NWcaFl__0q11k8ogFHZrA2?anonymous&ep=mcard") DASC 5100 — Course-Specific Learning Outcomes: Upon successful completion of this course, students will be able to: 1. Apply and use fundamental Python programming constructs such as iterations, lists, and dictionaries (G1.a). 2. Recognize and appreciate the extensive Python standard libraries and thousands of third-party open source libraries (G2.a). 3. Understand the strength and importance of the Python programming language in the fields of data science and machine learning(G2.a). 4. Use the Python programming language to solve real-world problems drawn from statistical context(G3.a, G1.b). 5. Appreciate the open-source nature of Python and the open source community (G2.a). Grading Policy: 6. Programming Assignments (8 assignments)= 20% of the course grade. 7. Quizzes (10 or more quizzes)= 20% of the course grade. 8. Discussions (8 discussions)= 10% of the course grade. 9. Midterm Exam= 20% of the course grade. 10. Seminars (5 recorded seminars) = 10% of the course grade. 11. Final Exam= 20% of the course grade. Grading Scale: >= 90.00 A 80.00-89.99 B 70.00-79.99 C 60.00-69.99 D 0.00-59.99 F The College of Science & Health is committed to giving regular and timely feedback to students to aid their progress toward achieving course learning goals. Normally, lab exercises, programming assignments, and quizzes will be graded within one week, and exams will be graded within two weeks, following their submission. Per College of Science & Health policy, students may not invoke an instructor’s failure to meet the above schedule for grading and providing feedback as the basis for a grade appeal. Course Schedule (Subject to Change): 2