برمجة حاسوب

MODULE DESCRIPTION FORM

نموذج وصف المادة الدراسية

Module Information معلومات المادة الدراسية
Module Title	Computer Programing				Module Delivery
Module Type	Core				☒ Theory ☒ Lecture ☒ Lab ☒ Tutorial ☐ Practical ☐ Seminar
Module Code	CHPR205
ECTS Credits	5
SWL (hr/sem)	150
Module Leve		UGx11 UGII	Semester of Delivery				3
Administering Department		CHPR	College	COGE
Module Leader	Ibrahim Naser Mahmood		e-mail	E-mail
Module Leader’s Acad. Title		Lecturer	Module Leader’s Qualification				MSc
Module Tutor	Name (if available)		e-mail	E-mail
Peer Reviewer Name		Name	e-mail	E-mail
Scientific Committee Approval Date		01/06/2023	Version Number			1.0

Relation with other Modules

العلاقة مع المواد الدراسية الأخرى

Prerequisite module

None

Semester

Co-requisites module

None

Semester

Module Aims, Learning Outcomes and Indicative Contents

أهداف المادة الدراسية ونتائج التعلم والمحتويات الإرشادية

Module Objectives

أهداف المادة الدراسية

Introduce the basics of information technology, computers, and their applications.
Familiarize students with the MATLAB interface and its features.
Teach fundamental programming concepts such as user input, output, variables, and operators.
Introduce conditional statements (if statements) for decision-making in programming.
Explore repetition structures (while loops, break, continue) for iterative tasks.
Learn about for loops and their applications in handling series and patterns.
Understand the concept of functions and debugging techniques.
Introduce vectors and matrices and their manipulation in MATLAB.
Explore string manipulation and its applications in programming.
Learn to work with images and perform basic image processing operations.
Demonstrate engineering applications of MATLAB in solving practical problems.

Module Learning Outcomes

مخرجات التعلم للمادة الدراسية

Proficiency in using MATLAB interface and executing basic commands.
Ability to write and debug MATLAB programs.
Competence in handling user input, output, variables, and operators.
Understanding of conditional statements and their application in decision-making.
Proficiency in using repetition structures (while loops, break, continue) for iterative tasks.
Ability to work with for loops and handle series and patterns.
Knowledge of functions and their implementation in MATLAB.
Competence in manipulating vectors and matrices in MATLAB.
Proficiency in string manipulation and its application in programming.
Understanding of basic image processing techniques using MATLAB.
Ability to apply MATLAB in solving engineering problems.

Indicative Contents

المحتويات الإرشادية

Indicative content includes the following.

Introduction to Information, Technology and Computers, MATLAB interface, user input and output, variables, operators, Selection – if statements, Repetition – while loops, break, continue, Repetition – for loops, Series and patterns, Functions / debugging, Vectors and Matrices , Strings, Images, Engineering Applications.

Learning and Teaching Strategies

استراتيجيات التعلم والتعليم

Strategies

The main strategy that will be adopted in delivering this module is to encourage students’ participation in the exercises, while at the same time refining and expanding their critical thinking skills. This will be achieved through classes, interactive tutorials and by considering types of simple experiments involving some sampling activities that are interesting to the students.

Student Workload (SWL)

الحمل الدراسي للطالب محسوب لـ ١٥ اسبوعا

Structured SWL (h/sem)

الحمل الدراسي المنتظم للطالب خلال الفصل

Structured SWL (h/w)

الحمل الدراسي المنتظم للطالب أسبوعيا

Unstructured SWL (h/sem)

الحمل الدراسي غير المنتظم للطالب خلال الفصل

Unstructured SWL (h/w)

الحمل الدراسي غير المنتظم للطالب أسبوعيا

Total SWL (h/sem)

الحمل الدراسي الكلي للطالب خلال الفصل

150

Module Evaluation تقييم المادة الدراسية
As		Time/Number	Weight (Marks)	Week Due	Relevant Learning Outcome
Formative assessment	Quizzes	2	10% (10)	5 and 10	LO #1, #2 and #3
	Assignments	2	20% (20)	2 and 12	LO #3, #4 and #5
	Projects / Lab.	8	10% (10)	Continuous	All
	Report	1	10% (10)	13	LO #4,and #5
Summative assessment	Midterm Exam	1.5hr	10% (10)	7	LO #1 - #4
Summative assessment	Final Exam	2hr	50% (50)	16	All
Total assessment			100% (100 Marks)

Delivery Plan (Weekly Syllabus) المنهاج الاسبوعي النظري
Week	Material Covered
Week 1	Introduction to information technology, computers, and MATLAB.
Week 2	MATLAB interface, user input, output, variables, and operators.
Week 3	Conditional statements (if statements) for decision-making.
Week 4	Repetition structures: while loops, break, and continue.
Week 5	Repetition structures: for loops and handling series and patterns.
Week 6	Functions and debugging techniques.
Week 7	Working with vectors and matrices in MATLAB.
Week 8	String manipulation and its application.
Week 9	Introduction to image processing and basic operations in MATLAB.
Week 10	Engineering applications of MATLAB: numerical computations.
Week 11	Engineering applications of MATLAB: data visualization.
Week 12	Engineering applications of MATLAB: curve fitting and regression analysis.
Week 13	Engineering applications of MATLAB: solving systems of equations.
Week 14	Engineering applications of MATLAB: optimization techniques.
Week 15	Engineering applications of MATLAB: simulation and modeling.
Week 16	Preparatory week before the final Exam

Delivery Plan (Weekly Lab. Syllabus) المنهاج الاسبوعي للمختبر
Week	Material Covered
Week 1	Introduction to MATLAB: Familiarize with the MATLAB environment, commands, and syntax.
Week 2	Basic Operations and Variables: Perform basic arithmetic operations, manipulate variables, and explore data types.
Week 3	Control Structures: Implement conditional statements (if-else) and loops (for, while) in MATLAB programs.
Week 4	Functions and Scripting: Create user-defined functions, understand function input and output, and work with script files.
Week 5	Vectors and Matrices: Perform vector and matrix operations, indexing, and element-wise calculations.
Week 6	Plotting and Visualization: Generate different types of plots, customize plot appearance, and add labels and annotations.
Week 7	File Input/Output: Read data from files, write data to files, and handle file formats such as CSV and Excel.
Week 8	Numerical Computations: Use MATLAB for solving numerical problems, numerical integration, and differentiation.
Week 9	Symbolic Computations: Explore symbolic mathematics in MATLAB for algebraic manipulations and solving equations.
Week 10	Image Processing: Apply basic image processing operations using MATLAB's image processing toolbox.
Week 11	Signal Processing: Perform basic signal processing tasks such as filtering, Fourier analysis, and spectral analysis.
Week 12	Optimization: Learn about optimization techniques in MATLAB for finding optimal solutions to problems.
Week 13	Curve Fitting and Regression Analysis: Fit curves to data, perform regression analysis, and evaluate model goodness-of-fit.
Week 14	Simulation and Modeling: Use MATLAB for building and simulating mathematical models in various domains.

Learning and Teaching Resources مصادر التعلم والتدريس
	Text	Available in the Library?
Required Texts	Title: "MATLAB: An Introduction with Applications" Author: Amos Gilat Publisher: Wiley Year: 2021	No
Recommended Texts	Title: "MATLAB for Engineers" Author: Holly Moore Publisher: Pearson Year: 2018	No
Websites	https://www.pearson.com/en-us/subject-catalog/p/Moore-MATLAB-for-Engineers-5th-Edition/P200000003249?view=educator

Grading Scheme مخطط الدرجات
Group	Grade	التقدير	Marks %	Definition
Success Group (50 - 100)	A - Excellent	امتياز	90 - 100	Outstanding Performance
	B - Very Good	جيد جدا	80 - 89	Above average with some errors
	C - Good	جيد	70 - 79	Sound work with notable errors
	D - Satisfactory	متوسط	60 - 69	Fair but with major shortcomings
	E - Sufficient	مقبول	50 - 59	Work meets minimum criteria
Fail Group (0 – 49)	FX – Fail	راسب (قيد المعالجة)	(45-49)	More work required but credit awarded
Fail Group (0 – 49)	F – Fail	راسب	(0-44)	Considerable amount of work required

Note: Marks Decimal places above or below 0.5 will be rounded to the higher or lower full mark (for example a mark of 54.5 will be rounded to 55, whereas a mark of 54.4 will be rounded to 54. The University has a policy NOT to condone "near-pass fails" so the only adjustment to marks awarded by the original marker(s) will be the automatic rounding outlined above.