Fall 2023
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: Ardan Yılmaz (ardanyilmaz - at - cs.hacettepe.edu.tr)
Time
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 |
|
|
Useful Links and Resources
(Web site in progress)