PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
EKNM 420	INTRODUCTION TO DATA ANALYTICS	3 + 0	6th Semester	5

COURSE DESCRIPTION

Course Level	Bachelor's Degree
Course Type	Elective
Course Objective	The aim of the course is to have basic knowledge about data cleaning, manipulating, processing and analysis.
Course Content	This course teaches the fundamental ideas to clean, manipulate, process, and analyze data. The students will work on data analysis problems arising in various data-intensive applications. The course involves many in-class coding exercises where the students are expected to work on several case studies. Through these exercises, the course shall also serve as an introduction to data analytics and modern scientific computing with Python programming language.
Prerequisites	No the prerequisite of lesson.
Corequisite	No the corequisite of lesson.
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

2	Work with Python’s conditional statements, functions, sequences, and loops
1	Learn how to code in Python
3	Learn how to use the data analysis toolkit, Pandas
4	Estimate univariate and multivariate regression analysis
5	Work with scientific packages, like NumPy
6	Plot graphs with Matplotlib

COURSE'S CONTRIBUTION TO PROGRAM

Data not found.

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	13	3	39
Hours for off-the-classroom study (Pre-study, practice)	13	3	39
Mid-terms	2	13	26
Final examination	2	13	26
Total Work Load ECTS Credit of the Course			130 5

COURSE DETAILS

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L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes

Prospective Student