Fall 2024

Course Information

This course covers the basic elements of data science life cycle, including statistics for data science, data exploration, data preprocessing, visualization, data analysis and inference. We will explore key areas including question formulation, data collection and cleaning, visualization, statistical inference, predictive modeling, and decision making. Specifically, we will focus on transforming, querying and analyzing data; basic algorithms for data analysis including regression, classification and clustering; principles behind creating informative data visualizations; and statistical concepts of measurement error and prediction.

Instructors

  • Nazli Ikizler-Cinbis (nazli - at - cs.hacettepe.edu.tr)
  • TA: Ahmet Alkılınç (ahmetalkilinc - at - cs.hacettepe.edu.tr)

Time

  • Tuesdays 13:00-15:30

Reference Books

Grading

AIN 212

Content Percentage
Midterm1 20%
Midterm2 25%
Project 15%
Final 40%

AIN 214

Content Percentage
Homeworks 15%+20%+20%+20%+25%

Announcements and Communications

All the announcements and communications will be carried out via Piazza, so please enroll to AIN212 Piazza link. The lecture notes will also be available in Piazza.

(Tentative) Schedule

Week Date Topic Lecture Notes Additional Reading(s)
1 04/10 Introduction to Data Science pdf  
2 11/10 Causality, Experiments, Tables in Python pdf  
3 18/10 Rectangular Data and Basic SQL    
4 25/10 SQL continued    
5 01/11 Data Cleaning, Reduction and Transformation    
6 08/11 Data Visualization    
7 15/11 Midterm 1    
8 22/11 Introduction to Statistical Inference and Regression    
9 29/11 Linear Models and Regression (cont’d)    
10 06/12 Classification and Logistic Regression    
11 13/12 Midterm 2    
12 20/12 Classification Trees    
13 27/12 Clustering    
14 03/01 Text, graphs and other data types    

(Web site in progress)