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

Tip: When working on assignments, use Ctrl+F on this page to search for a keyword and quickly find the relevant lecture. Click the “✏️ write” button to open a static version of the lecture for reference, which is much faster than loading it on DataHub.
Also, make sure to use the reference sheet to quickly look up babypandas methods and see examples of how they work.

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