View source for 数据科学基础 (Fall 2024)

{{Infobox
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|title        = <font size=3>'''数据科学基础'''<br>
Foundations of Data Science
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|header1 =Instructor
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|label2  = 
|data2   = '''尹一通'''
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|label3  = Email
|data3   = yinyt@nju.edu.cn  
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|label4  = office
|data4   = 计算机学院 804
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|label5  = 
|data5   = '''刘明谋'''
|header6 = 
|label6  = Email
|data6   = lmm@nju.edu.cn
|header7 =
|label7  = office
|data7   = 南雍-东207
|header8 = Class
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|data8   = 
|header9 =
|label9  = Class meeting
|data9   = Friday, 9am-12pm <br/>南雍-西311
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|label10 = Office hour
|data10  = Thursday, 6pm-8pm<br/>南雍-东207
|header11= Textbook
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|data11  = 
|header12=
|label12 = 
|data12  = [[File:概率导论.jpeg|border|100px]]
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|data13  = '''概率导论'''（第2版·修订版）<br> Dimitri P. Bertsekas and John N. Tsitsiklis<br> 郑忠国 童行伟 译；人民邮电出版社 (2022)
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|label14 = 
|data14  = [[File:Probability_and_Computing_2ed.jpg|border|100px]]
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|label15 = 
|data15  = '''Probability and Computing''' (2E) <br> Michael Mitzenmacher and Eli Upfal <br>   Cambridge University Press (2017)
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|label16 = 
|data16  = [[File:Foundations_of_Data_Science.jpg|border|100px]]
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|label17 = 
|data17  = '''Foundations of Data Science''' <br> Avrim Blum, John Hopcroft, Ravi Kannan <br>   Cambridge University Press (2020)
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This is the webpage for the ''Foundations of Data Science'' (数据科学基础) class of Fall 2024. Students who take this class should check this page periodically for content updates and new announcements. 

= Announcement =
* 因上课的同学太多，原教室无法容纳，从9月13日开始改为在西110上课。
* 因西110上课体验不太好，且已有部分同学退课，从9月29日开始重新<strong style="color:red;">回到西311上课</strong>。
* 9月20日修正了 [[数据科学基础 (Fall 2024)/Problem Set 1]] 中 Problem 1 的 [De Morgan’s Laws] 和 [<math>\sigma</math>-algebra] 的错误描述。
* 10月1日修正了 [[数据科学基础 (Fall 2024)/Problem Set 1]] 中 Problem 5 的 [Mutual independences] 的错误描述。
* 10月4日修改  [[数据科学基础 (Fall 2024)/Problem Set 1]] 中 Problem 3 的  [Symmetric 1D random walk (III)] 为选做题。没做出来不扣分。
* 10月11日添加了 [[数据科学基础 (Fall 2024)/Problem Set 2]] 中 Problem 1 的 [Cumulative distribution function (CDF)] 有关的定义，和 [Composing random variables] 有关的定义。
* 10月12日更新了已收到的第一次作业的名单。请同学们'''严格按照说明对文件进行命名'''，并'''使用邮件的附件提交作业'''，<strong style="color:red;">不要使用qq超大附件，它只是名字里带“附件”的网盘而不是附件</strong>，否则无法抓取到作业。仅抓取附件中以 "FA1.pdf" 结尾的文件。没有被抓取到作业的同学请联系助教重新提交。

= Course info =
* '''Instructor ''': 
** [http://tcs.nju.edu.cn/yinyt/ 尹一通]：[mailto:yinyt@nju.edu.cn <yinyt@nju.edu.cn>]，计算机学院 804 
** [https://liumingmou.github.io 刘明谋]：[mailto:lmm@nju.edu.cn <lmm@nju.edu.cn>]，南雍-东207
* '''Teaching assistant''':
** 周灿：[mailto:bzy.cirno@gmail.com 📧] 仙林校区计科楼北栋426 
** 陈弘毅：[mailto:502023330006@smail.nju.edu.cn 📧] 仙林校区计科楼北栋426
** 冯昱达：[mailto:yudafeng@smail.nju.edu.cn 📧] 仙林校区计科楼北栋426
** 丁天行：[mailto:652024330006@smail.nju.edu.cn 📧] 仙林校区计科楼北栋426
* '''Class meeting''':
** 周五：9am-12pm，南雍-<s>西311</s> <s>西110</s> <strong>西311</strong>
* '''Office hour''': 
:* 周四：6pm-8pm，南雍-东207（刘明谋）
:* '''QQ群''': 302709730（申请加入需提供姓名、院系、学号）

= Syllabus =
TBA

=== 教材与参考书 Course Materials ===
* '''[BT]''' 概率导论（第2版·修订版），[美]伯特瑟卡斯（Dimitri P.Bertsekas）[美]齐齐克利斯（John N.Tsitsiklis）著，郑忠国 童行伟 译，人民邮电出版社（2022）。
* '''[MU]''' ''Probability and Computing: Randomization and Probabilistic Techniques in Algorithms and Data Analysis'', by Michael Mitzenmacher, Eli Upfal; Cambridge University Press; 2nd edition (2017).
* '''[BHK]''' ''Foundations of Data Science'', by Avrim Blum, John Hopcroft, and Ravindran Kannan; Cambridge University Press (2020).

=== 成绩 Grading Policy ===
* 课程成绩：本课程将会有若干次作业和一次期末考试。最终成绩将由平时作业成绩和期末考试成绩综合得出。
* 迟交：如果有特殊的理由，无法按时完成作业，请提前联系授课老师，给出正当理由。否则迟交的作业将不被接受。

=== <font color=red> 学术诚信 Academic Integrity </font>===
学术诚信是所有从事学术活动的学生和学者最基本的职业道德底线，本课程将不遗余力的维护学术诚信规范，违反这一底线的行为将不会被容忍。

作业完成的原则：署你名字的工作必须是你个人的贡献。在完成作业的过程中，允许讨论，前提是讨论的所有参与者均处于同等完成度。但关键想法的执行、以及作业文本的写作必须独立完成，并在作业中致谢（acknowledge）所有参与讨论的人。符合规则的讨论与致谢将不会影响得分。不允许其他任何形式的合作——尤其是与已经完成作业的同学“讨论”。

本课程将对剽窃行为采取零容忍的态度。在完成作业过程中，对他人工作（出版物、互联网资料、其他人的作业等）直接的文本抄袭和对关键思想、关键元素的抄袭，按照 [http://www.acm.org/publications/policies/plagiarism_policy ACM Policy on Plagiarism]的解释，都将视为剽窃。剽窃者成绩将被取消。如果发现互相抄袭行为，<font color=red> 抄袭和被抄袭双方的成绩都将被取消</font>。因此请主动防止自己的作业被他人抄袭。

学术诚信影响学生个人的品行，也关乎整个教育系统的正常运转。为了一点分数而做出学术不端的行为，不仅使自己沦为一个欺骗者，也使他人的诚实努力失去意义。让我们一起努力维护一个诚信的环境。

= Assignments =
*[[数据科学基础 (Fall 2024)/Problem Set 1|Problem Set 1]]  请在 2024/10/11 上课之前(9:00 UTC+8)使用邮件的附件功能提交到 [mailto:pr2024_nju@163.com pr2024_nju@163.com] (文件名为'<font color=red >学号_姓名_FA1.pdf</font>').
** [[数据科学基础_(Fall_2024)/第一次作业提交名单|第一次作业提交名单]]
*[[数据科学基础 (Fall 2024)/Problem Set 2|Problem Set 2]]  请在 <s>2024/10/18</S> '''2024/10/25''' 上课之前(9:00 UTC+8)使用邮件的附件功能提交到 [mailto:pr2024_nju@163.com pr2024_nju@163.com] (文件名为'<font color=red >学号_姓名_FA2.pdf</font>').
*[[数据科学基础 (Fall 2024)/Problem Set 3|Problem Set 3]]  请在 2024/11/1 上课之前(9:00 UTC+8)使用邮件的附件功能提交到 [mailto:pr2024_nju@163.com pr2024_nju@163.com] (文件名为'<font color=red >学号_姓名_FA3.pdf</font>').

= Lectures =
# [http://tcs.nju.edu.cn/slides/FDS2024/Intro.pdf 课程简介]
# [http://tcs.nju.edu.cn/slides/FDS2024/ProbSpace.pdf 概率空间]
#* 阅读：'''[BT] 第1章'''
# [https://tcs.nju.edu.cn/wiki/images/0/04/数据科学基础_(Fall_2024)_RandVar.pdf 随机变量 (Rev 1)]
#* 阅读：'''[BT] 第2章''' 
#* 阅读：'''[MU] Chapter 2'''
#* [[数据科学基础 (Fall 2024)/Volume of Hamming balls|Volume of Hamming balls]]
#* [[数据科学基础 (Fall 2024)/Average-case analysis of QuickSort|Average-case analysis of '''''QuickSort''''']]
# [https://tcs.nju.edu.cn/wiki/images/9/94/数据科学基础_(Fall_2024)_Deviation-compressed.pdf  ‎偏差和矩 (Rev 2)]
#* 阅读：'''[MU] Chapter 3'''
#* 阅读：'''[BT] 章节 2.4, 4.2, 4.3, 5.1'''

= Concepts =
* [https://plato.stanford.edu/entries/probability-interpret/ Interpretations of probability]
* [https://en.wikipedia.org/wiki/History_of_probability History of probability]
* Example problems:
** [https://dornsifecms.usc.edu/assets/sites/520/docs/VonNeumann-ams12p36-38.pdf von Neumann's Bernoulli factory] and other [https://peteroupc.github.io/bernoulli.html Bernoulli factory algorithms]
** [https://en.wikipedia.org/wiki/Boy_or_Girl_paradox Boy or Girl paradox]
** [https://en.wikipedia.org/wiki/Monty_Hall_problem Monty Hall problem]
** [https://en.wikipedia.org/wiki/Bertrand_paradox_(probability) Bertrand paradox]
** [https://en.wikipedia.org/wiki/Hard_spheres Hard spheres model] and [https://en.wikipedia.org/wiki/Ising_model Ising model]
** [https://en.wikipedia.org/wiki/PageRank ''PageRank''] and stationary [https://en.wikipedia.org/wiki/Random_walk random walk]
** [https://en.wikipedia.org/wiki/Diffusion_process Diffusion process] and [https://en.wikipedia.org/wiki/Diffusion_model diffusion model]
*[https://en.wikipedia.org/wiki/Probability_space Probability space]
** [https://en.wikipedia.org/wiki/Sample_space Sample space]
** [https://en.wikipedia.org/wiki/Event_(probability_theory) Event] and [https://en.wikipedia.org/wiki/Σ-algebra <math>\sigma</math>-algebra]
** Kolmogorov's [https://en.wikipedia.org/wiki/Probability_axioms axioms of probability]
* [https://en.wikipedia.org/wiki/Discrete_uniform_distribution Classical] and [https://en.wikipedia.org/wiki/Geometric_probability goemetric probability]
* [https://en.wikipedia.org/wiki/Boole%27s_inequality Union bound]
** [https://en.wikipedia.org/wiki/Inclusion%E2%80%93exclusion_principle Inclusion-Exclusion principle]
** [https://en.wikipedia.org/wiki/Boole%27s_inequality#Bonferroni_inequalities Bonferroni inequalities]
* [https://en.wikipedia.org/wiki/Conditional_probability Conditional probability]
** [https://en.wikipedia.org/wiki/Chain_rule_(probability) Chain rule]
** [https://en.wikipedia.org/wiki/Law_of_total_probability Law of total probability]
** [https://en.wikipedia.org/wiki/Bayes%27_theorem Bayes' law]
* [https://en.wikipedia.org/wiki/Independence_(probability_theory) Independence] 
** [https://en.wikipedia.org/wiki/Pairwise_independence Pairwise independence]
* [https://en.wikipedia.org/wiki/Random_variable Random variable]
** [https://en.wikipedia.org/wiki/Cumulative_distribution_function Cumulative distribution function]
** [https://en.wikipedia.org/wiki/Probability_mass_function Probability mass function]
** [https://en.wikipedia.org/wiki/Probability_density_function Probability density function]
* [https://en.wikipedia.org/wiki/Multivariate_random_variable Random vector]
** [https://en.wikipedia.org/wiki/Joint_probability_distribution Joint probability distribution]
** [https://en.wikipedia.org/wiki/Conditional_probability_distribution Conditional probability distribution]
** [https://en.wikipedia.org/wiki/Marginal_distribution Marginal distribution]
* Some '''discrete''' probability distributions
** [https://en.wikipedia.org/wiki/Bernoulli_trial Bernoulli trial] and [https://en.wikipedia.org/wiki/Bernoulli_distribution Bernoulli distribution]
** [https://en.wikipedia.org/wiki/Discrete_uniform_distribution Discrete uniform distribution]
** [https://en.wikipedia.org/wiki/Binomial_distribution Binomial distribution]
** [https://en.wikipedia.org/wiki/Geometric_distribution Geometric distribution]
** [https://en.wikipedia.org/wiki/Negative_binomial_distribution Negative binomial distribution]
** [https://en.wikipedia.org/wiki/Hypergeometric_distribution Hypergeometric distribution]
** [https://en.wikipedia.org/wiki/Poisson_distribution Poisson distribution]
** and [https://en.wikipedia.org/wiki/List_of_probability_distributions#Discrete_distributions others]
* Balls into bins model
** [https://en.wikipedia.org/wiki/Multinomial_distribution Multinomial distribution]
** [https://en.wikipedia.org/wiki/Birthday_problem Birthday problem]
** [https://en.wikipedia.org/wiki/Coupon_collector%27s_problem Coupon collector]
** [https://en.wikipedia.org/wiki/Balls_into_bins_problem Occupancy problem]
* Random graphs
** [https://en.wikipedia.org/wiki/Erd%C5%91s%E2%80%93R%C3%A9nyi_model Erdős–Rényi random graph model]
** [https://en.wikipedia.org/wiki/Galton%E2%80%93Watson_process Galton–Watson branching process]
* [https://en.wikipedia.org/wiki/Expected_value Expectation]
** [https://en.wikipedia.org/wiki/Law_of_the_unconscious_statistician Law of the unconscious statistician, ''LOTUS'']
** [https://dlsun.github.io/probability/linearity.html Linearity of expectation]
** [https://en.wikipedia.org/wiki/Conditional_expectation Conditional expectation]
** [https://en.wikipedia.org/wiki/Law_of_total_expectation Law of total expectation]