CALCULUS-I
- Course
- MATH101 - CALCULUS-I
- Department
- Basic Sciences and Humanities
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 4
- ECTS
- 5
- T+P+L
- 3 + 0 + 2
- Course Coordinator(s)
- Dr. Mahir ALMATARNEH
- Prerequisite
- -
- Keywords
Course Description
Calculus-I provides the methods of differential and integral calculus with applications in geometry, physics and engineering. Students in this course will learn how to use mathematical language needed for applying the concepts of calculus to numerous applications in science and engineering such as identifying types of functions, graph of functions, evaluating limit of functions, limit of elementary functions (polynomial, trigonometric, logarithmic, exponential,…), methods to solve the undefined limits (L’Hopitals Rule), continuous functions, evaluating derivative of functions, definition of derivative, derivative of elementary functions, derivative of product of two functions and division of functions, applications of derivative, evaluate integrals of functions, definition of the integral, integral of elementary functions, substitution method, integration by parts, integral of rational functions, application of the integral (finding the area) .
CALCULUS-I
Evaluation Tools (Active Term)
| Item | Type | Weight (%) |
|---|---|---|
| Midterm | Midterm | 35 |
| Quiz | Quiz | 15 |
| Final | Final | 50 |
| Total | 100 | |
Course outcomes
- 01 Identify types of functions.
- 02 Calculate limits of functions.
- 03 Differentiate functions.
- 04 Draw the graph of a function.
- 05 Evaluate integrals of functions.
- 06 Use concepts of limit, derivative and integral in solving fundamental engineering problems.
Course Syllabus
| Week | Topic |
|---|---|
| Week 1 | Preliminaries. The Real number system and inequalities. Equations and lines. Functions. |
| Week 2 | Combining functions. Inverse functions. Trigonometric and inverse trigonometric functions. Exponential and logarithmic functions. |
| Week 3 | Limits and continuity. |
| Week 4 | The Derivative. Differantiation Rules. |
| Week 5 | Chain rule. Derivatives of trigonometric functions. |
| Week 6 | Derivatives of exponential and logarithmic functions. Implicit difefrantiation. |
| Week 7 | Midterm Week. |
| Week 8 | The Mean Value Theorem. Indeterminate forms and L'Hopital's rule. Extreme values of functions. |
| Week 9 | First and second derivative test. Curve sketching. |
| Week 10 | Antiderivatives. The definite integral. Calculating Areas. |
| Week 11 | Techniques of integration. Substitution method. Integration by parts. |
| Week 12 | Trigonometric substitution. Integration of rational functions using partial fractions. Improper integrals. |
| Week 13 | Final Week. |
| Week 14 | Final Week. |
| Week 15 | - |
Reference Books & Course Materials
- 01 Calculus Early Transcendental Functions, Robert T. Smith, Roland B. Mintin, 4th Edition, McGraw-Hill, ISBN 978-0-07-131656-9
- 02 Thomas' Calculus Early Transcendentals, George B. Thomas, M. D. Weir, J. Hass, F. R. Giordano, 12th Edition , Pearson.
- 03 Genel matematik 1, Prof dr. İbrahim Ethem Anar, Gazi Kitabevi,2013
- 04 Analiz 1, Prof. Dr. Mustafa Balcı, Balcı Yayınları.
Learning Outcomes
- L01 Identify types of functions. SOLO 0
- L02 Calculate limits of functions. SOLO 0
- L03 Differentiate functions. SOLO 0
- L04 Draw the graph of a function. SOLO 0
- L05 Evaluate integrals of functions. SOLO 0
- L06 Use concepts of limit, derivative and integral in solving fundamental engineering problems. SOLO 0
Program Outcomes
- P01 Apply data science principles and techniques to challenges in real life situations, and effectively communicate their solutions.
- P02 Identify and implement data analysis methodologies based on theoretical ideas, ethical code, and in-depth knowledge of the underlying data.
- P03 Analyze the guiding concepts and assessment procedures for information analysis in real-life applications.
- P04 Design and apply relevant data analysis models to find obscure solutions to business-related problems.
- P05 Utilize modern computing techniques to handle real-world problems characterized by massive amounts of data, such as parallel and distributed computing and machine learning.
- P06 Configure and administer the software tools required to efficiently produce usable information from any size of structured and unstructured datasets.
- P07 Administer or manage data science tools and techniques to organize and complete projects aimed at gaining useful insight from complex data.
- P08 Think critically and imaginatively, conceiving real-world issues from several angles, and work well in a variety of teams to solve issues cooperatively.
- P09 Be able to effectively integrate data‐based solutions into the user environment and help non-technical professionals in exploring, visualizing, and using these solutions
- P10 Understand their obligations under professional and ethical standards in relation to matters like data ownership and citation, data security and sensitivity and the privacy implications of data analysis.
Po-Lo Matrix
| LO | P01 | P02 | P03 | P04 | P05 | P06 | P07 | P08 | P09 | P10 | Average |
|---|---|---|---|---|---|---|---|---|---|---|---|
| L01 | - | - | - | - | - | - | - | - | - | - | - |
| L02 | - | - | - | - | - | - | - | - | - | - | - |
| L03 | - | - | - | - | - | - | - | - | - | - | - |
| L04 | - | - | - | - | - | - | - | - | - | - | - |
| L05 | - | - | - | - | - | - | - | - | - | - | - |
| L06 | - | - | - | - | - | - | - | - | - | - | - |