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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS MAT 2042 COMPUTER ALGEBRA SYSTEMS COMPULSORY 2 2 0 5

Offered By

Mathematics (English)

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

DOCTOR VOLKAN ÖĞER

Offered to

Mathematics (English) Mathematics (Evening)

Course Objective

This course aims to give information about necessary tools which doing mathematical computations by computer and writing results as a report.

Learning Outcomes of the Course Unit

1   To be able to prepare mathematical documents using LaTeX. 2   To be able to perform mathematical calculations using Python's sympy and numpy libraries. 3   To be able to perform mathematical calculations using Mathematica. 4   To be able define and solve mathematical problems with one of the softwares introduced.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 What is latex Structure of Latex, chaptering in Latex, text mode and math mode, writing equations. 2 Equation numbering, inserting images, creating tables, adding labels, cross-referencing, theorems, definitions, etc. 3 Preparing bibliography with Latex (bibtex), creating appendices, creating indexes, preparing presentations with Latex (beamer). 4 Basic structure of Mathematica notebook, variables, lists, arrays and defining functions in Mathematica. 5 Calculus (equations, differentiation, integral, arrays, series, limit) in Mathematica. 6 Linear algebra (vectors, matrices, systems of linear equations) in Mathematica. 7 Mathematica as a programming language: loop structures, control structures. 8 Midterm Exam and discussion on it. 9 Graphs (2D-3D) in Mathematica. 10 Basic structure of Jupyter notebook, introduction to the 'sympy' library. Defining symbolic variable. 11 Calculus (functions, equations, derivative, integral, sequences, series, limit) with 'sympy'. 12 Linear algebra (vectors, matrices, systems of linear equations) with 'sympy'. 13 Graphs (2D-3D) with 'sympy'. 14 Numerical operations with 'numpy'. 15 Mathematical problem solving examples with Mathematica and Python.

Recomended or Required Reading

Textbook(s): 1. The Latex Companion - Frank Mittelbach, Michel Goossens,..-2nd ed.,2004 2. Maple and Mathematica: A problem solving approach for mathematics - Shingareva, Inna K., Lizárraga-Celaya, Carlos-2nd ed., 2009,

Planned Learning Activities and Teaching Methods

Lecture notes, presentation and laboratory

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 ASG ASSIGNMENT 3 FIN FINAL EXAM 4 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.35 + ASG * 0.30 + FIN * 0.35 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.35 + ASG * 0.30 + RST * 0.35

Further Notes About Assessment Methods

HOMEWORK: Using LaTeX, to prepare a mathematical document that will meet predetermined conditions, using only the structures explained in the course.

Assessment Criteria

If your final grade or average is lower than 20, you will be excluded from evaluation and fail (FF).

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

volkan.oger@deu.edu.tr

Office Hours

Will be annunced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 2 28 Tutorials 14 2 28 Preparations before/after weekly lectures 14 2 28 Preparation for midterm exam 1 10 10 Preparing assignments 1 15 15 Preparation for final exam 1 10 10 Final 1 2 2 Midterm 1 2 2 TOTAL WORKLOAD (hours) 123

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 LO.1 3 5 LO.2 5 LO.3 5 LO.4 5