Patrice Koehl
Department of Computer Science
Genome Center
Room 4319, Genome Center, GBSF
451 East Health Sciences Drive
University of California
Davis, CA 95616
Phone: (530) 754 5121

AIX0008: AI+X: Introduction to Data Science 2022

General information


Week 1: June 27- Jul 1
Monday Tuesday Wednesday Thursday
16:00 - 19:00 Opening ceremony Lecture 1
Lecture 2
Lecture 3
Data (1)

Week 2: Jul 4- Jul 8
Monday Tuesday Wednesday Thursday
16:00 - 19:00 Lecture 4
Data (2)
Lecture 5
Data Exploration
Lecture 6
k-NN: Regression/ Classification
Lecture 7
Midterm; Market Societies

Week 3: Jul 11- Jul 15
Monday Tuesday Wednesday Thursday
16:00 - 19:00 Lecture 8
k-NN: Classification
Lecture 9
Linear Fit
Lecture 10
Lecture 11
Neural Network

Week 4: July 18- July 22
Monday Tuesday Wednesday Thursday Friday
16:00 - 19:00 Lecture 12
The machine stops
Lecture 13
Fairness in AI
Lecture 14
Oral presentations
Lecture 15
Oral presentations



Data science is an interdisciplinary field that uses scientific methods to extract knowledge and insights from possibly noisy, structured and unstructured data, and apply that knowledge across a broad range of application domains. Data science is related to data mining, machine learning, artificial intelligence, and big data. Data science is a term that is meant to unify statistics, data analysis, informatics, and their related methods in order to understand and analyse actual phenomena with data. It uses techniques and theories drawn from mathematics, statistics, computer science, information science, and domain knowledge. However, data science is different from computer science and information science.


  • What is data?
  • Machine learning: extracting information from data
  • What is Artificial intelligence?
  • Ethics: Big Data, Machine Learning, and Society

from Wikimedia

Being responsible for your grades

Grade breakdown

Attendance 5%
Homework 15%
Midterm 20%
Final (paper + oral presentation) 60%

Academic Conduct

The rules for conduct in classes can be summarized with three principles:

  • Be polite.
  • Don’t cheat.
  • Don’t lie.

Be polite

As adults meeting in a professional context, we should all behave professionally: this means being polite and respectful to everyone we deal with.

As the instructor, it is my responsibility to teach as well as I can and to be available, polite and respectful to you.

You are responsible for treating me and your fellow students politely and with respect.

Don’t cheat

As the instructor, it is my responsiblity to make tests and assignments that are fair, to grade fairly, to look for cheating, and to refer students who cheat for possible sanctions.

As students, it is your responsibility to avoid cheating and to discourage other students from cheating.

Don’t lie

Cheating is one form of lies, but there are other. Manipulating data, false claim of ownership of an assignment/idea, plagiarism are all forms of lies. Do not lie to the instructor, and even more importantly, do not lie to yourself!


  Page last modified 18 July 2022