PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
IENG 341	INTRODUCTION TO DATA ANALYTICS	3 + 0	6th Semester	5

COURSE DESCRIPTION

Course Level	Bachelor's Degree
Course Type	Elective
Course Objective	This course aims to provide an introduction to the data science and data analytics using the methods of statistical learning, an approach blending classical statistical methods with recent advances in computational and machine learning. The course will cover the main analytical methods from this field with hands-on applications using example datasets, so that students gain experience with and confidence in using the covered methods.
Course Content	Data Science and Big Data Analytics, Relational Databases and Data Modeling, Data Warehousing and Integration, Parallel Databases, Hadoop/ Mapreduce/Spark, Data Visualization, Machine Learning, Classification and Regression, Clustering, Natural Language Processing, Information Retrieval, Network Analysis
Prerequisites	No the prerequisite of lesson.
Corequisite	No the corequisite of lesson.
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

1	Learns the concepts of information and data practically.
2	Recognizes the fields of science in which data science is interdisciplinary
3	Learns the concept of big data.
4	Learns big data tools.

COURSE'S CONTRIBUTION TO PROGRAM

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	14	3	42
Assignments	4	6	24
Mid-terms	1	10	10
Final examination	1	14	14
Presentation / Seminar Preparation	1	14	14
Report / Project	1	26	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