Introduction to Data Science (CS 210)

2021 Fall
Faculty of Engineering and Natural Sciences
Computer Sci.& Eng.(CS)
3
6.00 / 6.00 ECTS (for students admitted in the 2013-14 Academic Year or following years)
Öznur Taştan Okan otastan@sabanciuniv.edu,
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English
Undergraduate
MATH203 IF100
Formal lecture,Interactive lecture,Recitation
Interactive,Project based learning
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CONTENT

Data science spans a large variety of disciplines and requires a collection of skills. This course is intended to tour the basic techniques of data science from manipulation and summarizing the important characteristics of a data set, basic statistical modeling, web programming and visualization. The assignments and term project will involve Python, JavaScript languages and open source tools such as R.

OBJECTIVE

Data science spans a large variety of disciplines and requires a collection of skills. This course is intended to tour the basic techniques of data science from manipulation and summarizing the important characteristics of a data set, basic statistical modeling, web programming and visualization.

LEARNING OUTCOME

Learning the fundamentals of data science pipeline
Learning how to explore and experiment with data
Learn basic statistics (sampling techniques, mean, variance, outliers, Central Limit theorem, distributions) and machine learning techniques (clustering) that are necessary to analyze data: big and small
Perform a statistical analysis on sample socio-economic data
Building an understanding of data analytics techniques (data collection, cleaning, exploratory techniques, modeling and presentation)
Develop competency in the Python programming language within the course project
Design and run experimental tests to evaluate hypotheses about data

ASSESSMENT METHODS and CRITERIA

  Percentage (%)
Final 30
Group Project 20
Homework 40
Other 10

RECOMENDED or REQUIRED READINGS

Readings

There will be weekly papers as readings distributed.