Course Syllabus
Below is a syllabus template that includes WSU's required syllabus elements. Please complete all items highlighted in yellow.
Title of Course Computational Calculus II
Prefix and Number DATA 122
Semester and Year Fall 2025
Number of Credit Hours 3
Prerequisites DATA 121 with a C or better or MATH 171 with a C or better.
Course Details
Day and Time: [tbd]
Meeting Location: [tbd]
Instructor Contact Information
Instructor Name: [tbd]
Instructor Contact Information: [office location, phone, email] [tbd]
Instructor Office Hours: [click here for best practices] [tbd]
TA Name: [tbd]
TA Contact Information: [office location, phone, email]: [tbd]
TA Office Hours: [click here for best practices] [tbd]
Course Description
This course introduces the fundamental concepts of calculus, including limits, derivatives, integrals, and their applications, with a strong emphasis on computational methods using Python. The course is tailored for students majoring in Data Analytics, focusing on the practical implementation of algorithms to solve complex problems. Hands-on projects utilizing Python libraries will enhance understanding and application of calculus in real-world data analytics scenarios.
Course Materials
Books: N/A
Reference Materials: ‘Calculus: A Modeling and Computational Thinking Approach’ by E. Stade and E. Stade, Springer, 1st Edition, 2023. E-ISBN: 978-3-031-24681-4. URL: https://link.springer.com/book/10.1007/978-3-031-24681-4
‘Computational Calculus: A Numerical Companion to Elementary Calculus’ by W. C. Bauldry, Springer, 1st Edition, 2023. E-ISBN: 978-3-031-29658-1. URL: https://link.springer.com/book/10.1007/978-3-031-29658-1
Fees: N/A
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Course Learning Outcomes (students will be able to:) |
Activities Supporting the Learning Outcomes | Assessment of the Learning Outcomes |
|---|---|---|
|
Understand and apply the concepts of limits, derivatives, and integrals. |
[insert] |
All four project assignments listed in the Grading section assess a mixture of all the 5 SLOs. |
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Implement numerical methods for differentiation and integration using Python. |
[insert] |
All four project assignments listed in the Grading section assess a mixture of all the 5 SLOs. |
| Utilize Python libraries to solve calculus problems, with a focus on data analytics applications. |
[insert] |
All four project assignments listed in the Grading section assess a mixture of all the 5 SLOs. |
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Analyze and interpret the results of computational methods in the context of data modeling. |
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All four project assignments listed in the Grading section assess a mixture of all the 5 SLOs. |
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Apply calculus concepts to real-world scenarios through project-based learning. |
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All four project assignments listed in the Grading section assess a mixture of all the 5 SLOs. |
| Dates | Lesson Topic | Assignment | Assessment |
|---|---|---|---|
| Week 8/9 [dates] |
Multivariable Calculus | [insert] |
Partial Derivatives and Gradient Vectors Modular Programming and Arrays Multiple Integrals (Double and Triple Integrals) with applications in Data Analytics Applying Multivariable Calculus to optimize functions using Python |
| Week 10 [dates] |
Optimization Techniques | [insert] |
Optimization with Lagrange Multipliers Lists and Strings Applications in Constrained Optimization Problems Solving optimization problems using Python |
| Week 11 [dates] |
Vector Calculus | [insert] |
Vector Fields, Divergence, and Curl Structures and Recursion Line Integrals and Green’s Theorem Visualizing and analyzing vector fields using Python |
| Week 12 [dates] |
Parametric and Polar Coordinates | [insert] |
Parametric Equations and Polar Coordinates Dynamic Data Structures and Command Line Arguments Applications in Data Visualization and Analytics Visualizing complex data using parametric and polar plots |
| Week 13-16 [dates] |
Final Project | [insert] |
Final Project: Students choose a real-world problem to solve using computational calculus techniques with Python, focusing on Data Analytics applications. |
Expectations for Student Effort
[Describe how much time students should expect to invest in the course each week. Graduate courses should state: "For each hour of lecture equivalent, students should expect to have a minimum of two hours of work outside of class." Note that Global campus courses will automatically include credit hour equivalents in the syllabus.]
Students should expect to spend a minimum of 3 hours per week for each online 1-credit course, engaged in the following types of activities: reading, listening to/viewing media, discussion, or conversation in the LMS or other academic technology, conducting research, completing assignments, and reviewing instructor feedback, studying for and completing assessments, etc.
Grading [add more lines if necessary]
| Type of Assignment (tests, papers, etc) | Points | Percent of Overall Grade |
|---|---|---|
|
Project 1: Multivariable Calculus |
[insert] |
20% |
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Project 2: Optimization Techniques |
[insert] |
20% |
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Project 3: Vector Calculus |
[insert] |
20% |
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Project 4: Parametric and Polar Plots |
20% |
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Project 5: Final Project |
20% |
Performance metrics for assignments vary from one assignment to another. These metrics are listed in the assignment descriptions available on the LMS.
Course assignments and their due dates will be made available on the LMS.
| Grade | Percent | Grade | Percent |
|---|---|---|---|
| A |
94 — 100 |
C |
74 — 76.9 |
| A- |
90 — 93.9 |
C- |
70 — 73.9 |
| B+ |
87 — 89.9 |
D+ |
67 — 69.9 |
| B |
84 — 86.9 |
D |
61 — 66.9 |
| B- |
80 — 83.9 |
F |
0 — 60.9 |
| C+ |
77 — 79.9 |
Letter grades will be assigned based on the scale shown below. The assignment and exam scores will be adjusted (curved) according to the class averages. The scale assumes class average is 80%.
Attendance and Make-Up Policy
[Provide details on how attendance affects final course grades. Indicate whether and how missed exams, laboratory sessions, etc. can be made up. Sample attendance statement: “Students should make all reasonable efforts to attend all class meetings. However, in the event a student is unable to attend a class, it is the responsibility of the student to inform the instructor as soon as possible, explain the reason for the absence (and provide documentation, if appropriate), and make up class work missed within a reasonable amount of time, if allowed. Missing class meetings may result in reducing the overall grade in the class.” ]
The course will be delivered in a hybrid fashion. As such, attendance is not required. The instructor expects the students to be mature enough to be able to manage the course items as per the course schedule listed in the LMS.
Academic Integrity Statement
You are responsible for reading WSU's Academic Integrity Policy, which is based on Washington State law. If you cheat in your work in this class you will:
-[insert your sanction here]
-Be reported to the Center for Community Standards
-Have the right to appeal my decision
-Not be able to drop the course of withdraw from the course until the appeals process is finished
If you have any questions about what you can and cannot do in this course, ask me.
If you want to ask for a change in my decision about academic integrity, use the form at the Center for Community Standards website. You must submit this request within 21 calendar days of the decision.