Data 100: Principles and Techniques of Data Science

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课程资源

课程主页 Home / Schedule - Data 100 (ds100.org)

课程仓库：DS-100/sp22: sp22 public facing repo (github.com)

书籍 Learning Data Science — Learning Data Science (learningds.org)

本人作业、实验及项目仓库：BaiRuic/data100_sp22 (github.com)

Data Science is the application of data centric, computational, and inferential thinking to :

understand the word (science)

slove the problems (engineering)

Principles and Techniques of Data Science

Name

Type

Recording

Slides

1️⃣

Course Overview

Lecture

YoububeRecording

GoogleSlide

1️⃣

Data Sampling and Probability

Lecture

YouTubeRecording

GoogleSlide

1️⃣

DISCUSSION 1

Discussion

LAB

Pandas I

Lecture

Lecture

DISCUSSION 2

Discussion

LAB

Data Wrangling, EDA

Lecture

Lecture

DISCUSSION 3

Discussion

LAB

Visualizations

Lecture

recording

slides

4️⃣

Visualizations II

Lecture

Discussion

LAB

Intro to Modeling, Simple Linear Regression

Lecture

youtube

slide

5️⃣

Constant Model, Loss, and Transformations

Lecture

recording

slides

5️⃣

Lab5: Modeling, Summary Statistics, Loss Functions

LAB

6️⃣

Lecture 11 – Ordinary Least Squares

Lecture

YouTube

Slide

6️⃣

Lab6: Ordinary Least Squares

LAB

7️⃣

Lecture 12 – Gradient Descent, sklearn

Lecture

YouTube

• slides

7️⃣

Lecture 13 – Gradient Descent, Feature Engineering

Lecture

YouTube

slides

7️⃣

DISCUSSION 7 Human Contexts in Engineering and Feature Engineering

Discussion

recording

GoogleDriver

7️⃣

LAB 7 Gradient Descent and sklearn

LAB

7️⃣

PROJ 1A Housing I

Proj

8️⃣

Lecture 14 – Case Study (HCE): Fairness in Housing Appraisal

Lecture

video playlist

slides

8️⃣

Lecture 15 – Cross Validation, Regularization

Lecture

recording

slides

8️⃣

LAB 8 Model Selection, Regularization, and Cross-Validations

LAB

8️⃣

PROJ 1B Housing II

Proj

9️⃣

LECTURE 16 Probability I: Random Variables

Lecture

recording

slides

9️⃣

Lecture 17 – Probability II: Estimators, Bias, and Variance

Lecture

• recording

• slides

9️⃣

LAB 9 Probability and Modeling

LAB

9️⃣

HOMEWORK 6 Probability and Estimators

🔟

Lecture 18 – SQL I

Lecture

• recording

• slides

🔟

Lecture 19 – SQL II and PCA I

Lecture

• recording

• slides

🔟

LAB 10 SQL

LAB

🔟

HOMEWORK 7 SQL and PCA

Lecture 20 – Principal Component Analysis (PCA) II

Lecture

• recording

• slides

LAB 11 PCA

LAB

LECTURE 21 Classification and Logistic Regression I

Lecture

recording

slides

Lecture 22 – Logistic Regression II

Lecture

• recording

• slides

LAB 12 Logistic Regression

LAB

PROJ 2A Spam & Ham I

Proj

LECTURE 23 Decision Trees

Lecture

• recording

• slides

LECTURE 24 Clustering

Lecture

• recording

• slides

LAB 13 Decision Trees & Random Forest

LAB

PROJ 2B Spam & Ham II

Proj

Lecture 25 - Data Regulations

Lecture

• recording

• slides

Lecture 26 - Guest Speaker Matei Zaharia: Parallel Data Analytics; Conclusion

Lecture

• recording

slides，slides

LAB 14 Clustering

LAB

HOMEWORK 8 Taxis