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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS FSH 0045 INTRODUCTION TO PROGRAMMING WITH PYTHON ELECTIVE 2 0 0 2

Offered By

Faculty Of Science

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR EMEL KURUOĞLU KANDEMIR

Offered to

Biology Chemistry Computer Science Statistics Mathematics Physics

Course Objective

Dersin amacı, Python'da programlamanın nasıl yapılacağını öğretmektir.

Learning Outcomes of the Course Unit

1   Have a good understanding about the concept of the algorithm. 2   Have a basic knowledge of data types. 3   Have ability to use computer programming structures. 4   Have ability to design and test application codes in Python programming language.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction 2 Python Development Environment 3 Input/output and Variables 4 Operators 5 Conditional Statements 6 Conditional Statements (cont.) 7 Useful statistical models, discrete distributions 8 Mid-term exam 9 Loops 10 Loops (cont.) 11 Arrays 12 Strings 13 Lists 14 Functions

Recomended or Required Reading

Yeni Başlayanlar Için Python,Ahmet Aksoy, Abaküs Kitap

Planned Learning Activities and Teaching Methods

The course is taught in a lecture, class presentation and discussion format.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 FIN FINAL EXAM 3 FCG FINAL COURSE GRADE MTE * 0.40 + FIN * 0.60 4 RST RESIT 5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + FIN * 0.60 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

efendi.nasibov@deu.edu.tr

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 2 26 Preparations before/after weekly lectures 12 2 24 Final 1 2 2 Midterm 1 2 2 TOTAL WORKLOAD (hours) 54

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 5 4 5 3 5 5 4 5 5 LO.2 5 5 5 2 5 4 5 5 LO.3 5 5 4 3 5 5 LO.4 5 5 3 3 2 2 5 5