Principles of Data Science

DSC 10, Fall 2025 at UC San Diego

Peter Chi
he/him

pbchi@ucsd.edu

Lecture(s): (D) MWF 9-9:50AM in PODEM 1A19

Janine Tiefenbruck
she/her

jlobue@ucsd.edu

Lecture(s): (A) MWF 9-9:50AM, (B) MWF 10-10:50AM, (C) MWF 11-11:50AM in PCYNH 106

Jump to the current week

Week 0 – Welcome to DSC 10!

Fri Sep 26

LEC 1 Introduction

CIT 1.0-1.3

Keywords: data science, course structure, policies, syllabus, Little Women demo

Sat Sep 27

SUR Welcome Survey

SYL Syllabus Check

Week 1 – Python Basics

Mon Sep 29

LEC 2 Expressions and Data Types

BPD 1-6

Keywords: Jupyter notebooks, expressions, variables, assignment, functions, int, float

DISC 1 Getting Started with Jupyter Notebooks

Wed Oct 1

LEC 3 Strings, Lists, and Arrays

BPD 7-8, CIT 14.1

Keywords: string methods, mean, median, lists, arrays, array arithmetic

POD Pod Meeting

Thu Oct 2

PRE Pretest

LAB 0 Expressions and Data Types

Fri Oct 3

LEC 4 Arrays and DataFrames

BPD 9

Keywords: array methods, np.arange, .read_csv, .get, .assign, .sort_values, .iloc, .loc, index

Week 2 – DataFrames and Visualization

Mon Oct 6

LEC 5 Querying and Grouping

BPD 10-11

Keywords: .set_index, Booleans, querying, .shape, &, |, .take, .groupby, aggregation

DISC 2 Arrays and DataFrames

Wed Oct 8

LEC 6 Grouping and Data Visualization

CIT 7.0-7.1

Keywords: .groupby, numerical vs. categorical, scatter plot, line plot, bar chart

POD Pod Meeting

Thu Oct 9

LAB 1 Arrays and DataFrames

Fri Oct 10

LEC 7 Distributions and Histograms

CIT 7.2-7.3

Keywords: distributions, density histograms, binning, total area, overlaid plots

Sat Oct 11

HW 1 Basic Python, Arrays, and DataFrames

Week 3 – Functions and Control Flow

Mon Oct 13

LEC 8 Functions and Applying

BPD 6, 12

Keywords: functions, arguments, print vs. return, .apply, .reset_index

DISC 3 Querying, Grouping, and Plotting

Wed Oct 15

LEC 9 Grouping on Multiple Columns, Merging

BPD 11, 13

Keywords: .groupby([col_1, col_2, …]), subgroups, MultiIndex, .merge, number of rows

QUIZ 1 Quiz 1 covers Lectures 1-5

Thu Oct 16

LAB 2 Data Visualizations and Functions

Fri Oct 17

LEC 10 Conditional Statements and Iteration

CIT 9.0-9.2

Keywords: in, not, and, or, if, else, elif, for-loops, np.append, accumulator pattern

Sat Oct 18

HW 2 DataFrames, Data Visualization, and Functions

Week 4 – Probability and Simulation

Mon Oct 20

LEC 11 Probability

CIT 9.5

Keywords: event, conditional prob., multiplication and addition rules, independence

DISC 4 Functions, DataFrames, and Control Flow

Wed Oct 22

LEC 12 Simulation

CIT 9.3-9.4

Keywords: np.random.choice, replacement, np.count_nonzero, coin flipping, Monty Hall

QUIZ 2 Quiz 2 covers Lectures 6-10

Thu Oct 23

LAB 3 DataFrames, Control Flow, and Probability

Fri Oct 24

LEC 13 Distributions and Sampling

CIT 10.0-10.4

Keywords: probability vs. empirical distribution, SRS, .sample, parameter, statistic

Sat Oct 25

HW 3 DataFrames, Control Flow, and Probability

SUR Mid-Quarter Survey

Week 5 – Midterm Exam

Mon Oct 27

REV Midterm Review

DISC 5 Probability and Simulation

Wed Oct 29

EXAM Midterm Exam covers Lectures 1-12

POD Pod Meeting

Fri Oct 31

LEC 14 Bootstrapping and Confidence Intervals

CIT 13.0-13.2

Keywords: inference, bootstrapping, resample, np.percentile, confidence interval

Sat Nov 1

PROJ Midterm Project

Week 6 – Confidence Intervals and the Normal Distribution

Mon Nov 3

LEC 15 Confidence Intervals, Center, and Spread

CIT 13.3-13.4

Keywords: interpreting CIs, robust vs. sensitive, center, standard deviation

DISC 6 Sampling, Bootstrapping, and Confidence Intervals

Wed Nov 5

LEC 16 Standardization and the Normal Distribution

CIT 14.2-14.3

Keywords: Chebyshev, standard units, normal distribution, CDF, inflection points

POD Pod Meeting

Thu Nov 6

LAB 4 Simulation, Sampling, & Bootstrapping

Fri Nov 7

LEC 17 The Central Limit Theorem

CIT 14.4-14.5

Keywords: distribution of the sample mean, square root law, CLT-based CIs

Sat Nov 8

HW 4 Simulation, Sampling, Bootstrapping

Week 7 – Central Limit Theorem

Mon Nov 10

LEC 18 Choosing Sample Sizes, Statistical Models

CIT 14.6, 11.1

Keywords: standard deviation of 0s and 1s, np.random.multinomial, Robert Swain jury

DISC 7 Standardization and the Normal Distribution

Wed Nov 12

LEC 19 Hypothesis Testing

CIT 11.3

Keywords: null and alternative hypotheses, test statistic, fair or unfair coin

QUIZ 3 Quiz 3 covers Lectures 13-15

Thu Nov 13

LAB 5 Variability and the Normal Distribution

Fri Nov 14

LEC 20 Hypothesis Testing and Total Variation Distance

CIT 11.2, 11.4

Keywords: fair or unfair coin, p-value, midterm exam scores, Alameda County jury, TVD

Sat Nov 15

HW 5 The Normal Distribution and the Central Limit Theorem

Week 8 – Hypothesis and Permutation Testing

Mon Nov 17

LEC 21 TVD, Hypothesis Testing, and Permutation Testing

CIT 12.0-12.1

Keywords: confidence intervals for hypothesis testing, body temperature, smoking/babies

DISC 8 The CLT and Hypothesis Testing

Wed Nov 19

LEC 22 Permutation Testing

CIT 12.3

Keywords: smoking/babies, np.random.permutation, shuffling, Deflategate

QUIZ 4 Quiz 4 covers Lectures 16-18

Thu Nov 20

LAB 6 Hypothesis Testing

Fri Nov 21

LEC 23 Correlation

CIT 15.0-15.2

Keywords: association, correlation coefficient (r), predicting heights, regression line (su)

Week 9 – Prediction

Mon Nov 24

LEC 24 Regression and Least Squares

CIT 15.2-15.4

Keywords: regression line in original units, outliers, errors, RMSE, best fit, least squares

DISC 9 Total Variation Distance and Permutation Testing

Tue Nov 25

HW 6 Hypothesis Testing and Permutation Testing

Wed Nov 26

LEC 25 Residuals and Inference

CIT 15.5-16.3

Keywords: residuals, residual plots, patterns, datasaurus dozen, prediction intervals

Fri Nov 28

No Lecture (Thanksgiving Break🦃)

Week 10 – Review

Mon Dec 1

REV Review

DISC 10 Regression

Tue Dec 2

LAB 7 Regression

Wed Dec 3

REV Review

QUIZ 5 Quiz 5 covers Lectures 19-22

Thu Dec 4

PROJ Final Project

Fri Dec 5

REV Review, Conclusion

Sat Dec 6

EXAM Final Exam (3-6PM)

SUR SETs and End-of-Quarter Survey (due 8AM)

Principles of Data Science

Peter Chihe/him

Janine Tiefenbruckshe/her

Week 0 – Welcome to DSC 10!

Week 1 – Python Basics

Week 2 – DataFrames and Visualization

Week 3 – Functions and Control Flow

Week 4 – Probability and Simulation

Week 5 – Midterm Exam

Week 6 – Confidence Intervals and the Normal Distribution

Week 7 – Central Limit Theorem

Week 8 – Hypothesis and Permutation Testing

Week 9 – Prediction

Week 10 – Review

Peter Chi
he/him

Janine Tiefenbruck
she/her