Home
Explore Uedu
Student Console
Register as Member/Login
(2) In future presentations of the research findings, in addition to the course project website and public presentations, your real name and personal information will not appear in this research report. If you are interested in the research results, we can provide you with an executive summary after the study is completed.
問卷中心
Teacher Console
Course Setup
Support & Messages
Uptime Data

UeduGPTs

--

Jupyters

0

Local AI

--

CISOSE26 本地 AI UG26
政治大學 AQI 24 29°C

AI Reply Desktop Notifications

Show a desktop notification when the AI TA finishes replying

Chat Message Notifications

Notify me when classmates post messages in the forum

Sound notification

Play an alert sound whenever there is a new notification

Uedu Open / Mathematics for Computer Science
6.042J

Mathematics for Computer Science

Prof. Ronitt Rubinfeld, Prof. Albert R. Meyer | Fall 2005
Data Science, Analytics & Computer Technology Computer Science Science & Math Mathematics Engineering Applied Mathematics Discrete Mathematics Probability and Statistics
前往原始課程
CC BY-NC-SA 4.0
課程簡介

This is an introductory course in Discrete Mathematics oriented toward Computer Science and Engineering. The course divides roughly into thirds:

  1. Fundamental Concepts of Mathematics: Definitions, Proofs, Sets, Functions, Relations
  2. Discrete Structures: Modular Arithmetic, Graphs, State Machines, Counting
  3. Discrete Probability Theory

A version of this course from a previous term was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5512 (Mathematics for Computer Science).

Course Information
SourceMIT 開放式課程
科系Electrical Engineering and Computer Science
LanguageEnglish
影片數136
課程影片 (136)
1
1.1.1 Welcome to 6.042
1.1.1 Welcome to 6.042
1
Lec 1 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 1 | MIT 6.042J Mathematics for Computer Science, Fall 2010
2
1.1.2 Intro to Proofs: Part 1
1.1.2 Intro to Proofs: Part 1
2
Lec 2 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 2 | MIT 6.042J Mathematics for Computer Science, Fall 2010
3
1.1.3 Intro to Proofs: Part 2
1.1.3 Intro to Proofs: Part 2
3
Lec 3 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 3 | MIT 6.042J Mathematics for Computer Science, Fall 2010
4
1.2.1 Proof by Contradiction
1.2.1 Proof by Contradiction
4
Lec 4 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 4 | MIT 6.042J Mathematics for Computer Science, Fall 2010
5
1.2.3 Proof by Cases
1.2.3 Proof by Cases
5
Lec 5 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 5 | MIT 6.042J Mathematics for Computer Science, Fall 2010
6
1.3.1 Well Ordering Principle 1: Video
1.3.1 Well Ordering Principle 1: Video
6
Lec 6 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 6 | MIT 6.042J Mathematics for Computer Science, Fall 2010
7
1.3.3 Well Ordering Principle 2: Video
1.3.3 Well Ordering Principle 2: Video
7
Lec 7 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 7 | MIT 6.042J Mathematics for Computer Science, Fall 2010
8
1.3.5 Well Ordering Principle 3: Video
1.3.5 Well Ordering Principle 3: Video
8
Lec 8 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 8 | MIT 6.042J Mathematics for Computer Science, Fall 2010
9
1.4.1 Propositional Operators: Video
1.4.1 Propositional Operators: Video
9
Lec 9 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 9 | MIT 6.042J Mathematics for Computer Science, Fall 2010
10
1.4.3 Digital Logic: Video
1.4.3 Digital Logic: Video
10
Lec 10 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 10 | MIT 6.042J Mathematics for Computer Science, Fall 2010
11
1.4.4 Truth Tables: Video
1.4.4 Truth Tables: Video
11
Lec 11 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 11 | MIT 6.042J Mathematics for Computer Science, Fall 2010
12
1.5.1 Predicate Logic 1: Video
1.5.1 Predicate Logic 1: Video
12
Lec 12 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 12 | MIT 6.042J Mathematics for Computer Science, Fall 2010
13
1.5.2 Predicate Logic 2: Video
1.5.2 Predicate Logic 2: Video
13
Lec 13 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 13 | MIT 6.042J Mathematics for Computer Science, Fall 2010
14
1.5.4 Predicate Logic 3: Video
1.5.4 Predicate Logic 3: Video
14
Lec 14 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 14 | MIT 6.042J Mathematics for Computer Science, Fall 2010
15
1.6.1 Sets Definitions: Video
1.6.1 Sets Definitions: Video
15
Lec 15 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 15 | MIT 6.042J Mathematics for Computer Science, Fall 2010
16
1.6.2 Sets Operations: Video
1.6.2 Sets Operations: Video
16
Lec 16 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 16 | MIT 6.042J Mathematics for Computer Science, Fall 2010
17
1.7.1 Relations: Video
1.7.1 Relations: Video
17
Lec 17 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 17 | MIT 6.042J Mathematics for Computer Science, Fall 2010
18
1.7.3 Relational Mappings: Video
1.7.3 Relational Mappings: Video
18
Lec 18 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 18 | MIT 6.042J Mathematics for Computer Science, Fall 2010
19
1.7.5 Finite Cardinality: Video
1.7.5 Finite Cardinality: Video
19
Lec 19 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 19 | MIT 6.042J Mathematics for Computer Science, Fall 2010
20
1.8.1 Induction: Video
1.8.1 Induction: Video
20
Lec 20 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 20 | MIT 6.042J Mathematics for Computer Science, Fall 2010
21
1.8.2 Bogus Induction: Video
1.8.2 Bogus Induction: Video
21
Lec 21 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 21 | MIT 6.042J Mathematics for Computer Science, Fall 2010
22
1.8.4 Strong Induction: Video
1.8.4 Strong Induction: Video
22
Lec 22 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 22 | MIT 6.042J Mathematics for Computer Science, Fall 2010
23
1.8.6 WOP vs Induction: Video [optional]
1.8.6 WOP vs Induction: Video [optional]
23
Lec 23 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 23 | MIT 6.042J Mathematics for Computer Science, Fall 2010
24
1.9.1 State Machines Invariants: Video
1.9.1 State Machines Invariants: Video
24
Lec 24 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 24 | MIT 6.042J Mathematics for Computer Science, Fall 2010
25
1.9.3 Derived Variables: Video
1.9.3 Derived Variables: Video
25
Lec 25 | MIT 6.042J Mathematics for Computer Science, Fall 2010
Lec 25 | MIT 6.042J Mathematics for Computer Science, Fall 2010
26
1.10.1 Recursive Data: Video
1.10.1 Recursive Data: Video
27
1.10.4 Structural Induction: Video
1.10.4 Structural Induction: Video
28
1.10.7 Recursive Functions: Video
1.10.7 Recursive Functions: Video
29
1.11.1 Cardinality: Video
1.11.1 Cardinality: Video
30
1.11.3 Countable Sets: Video
1.11.3 Countable Sets: Video
31
1.11.4 Cantor's Theorem: Video
1.11.4 Cantor's Theorem: Video
32
1.11.7 The Halting Problem: Video [Optional]
1.11.7 The Halting Problem: Video [Optional]
33
1.11.9 Russell's Paradox: Video
1.11.9 Russell's Paradox: Video
34
1.11.11 Set Theory Axioms: Video [Optional]
1.11.11 Set Theory Axioms: Video [Optional]
35
2.1.1 GCDs & Linear Combinations: Video
2.1.1 GCDs & Linear Combinations: Video
36
2.1.2 Euclidean Algorithm: Video
2.1.2 Euclidean Algorithm: Video
37
2.1.4 Pulverizer: Video
2.1.4 Pulverizer: Video
38
2.1.6 Revisiting Die Hard: Video
2.1.6 Revisiting Die Hard: Video
39
2.1.7 Prime Factorization: Video
2.1.7 Prime Factorization: Video
40
2.2.1 Congruence mod n: Video
2.2.1 Congruence mod n: Video
41
2.2.3 Inverses mod n: Video
2.2.3 Inverses mod n: Video
42
2.3.1 Modular Exponentiation Euler's Function: Video
2.3.1 Modular Exponentiation Euler's Function: Video
43
2.3.3 The Ring Z: Video
2.3.3 The Ring Z: Video
44
2.4.1 RSA Public Key Encryption: Video
2.4.1 RSA Public Key Encryption: Video
45
2.4.3 Reducing Factoring To SAT: Video
2.4.3 Reducing Factoring To SAT: Video
46
2.5.1 Digraphs: Walks & Paths: Video
2.5.1 Digraphs: Walks & Paths: Video
47
2.5.3 Digraphs: Connected Vertices: Video
2.5.3 Digraphs: Connected Vertices: Video
48
2.6.1 DAGs: Video
2.6.1 DAGs: Video
49
2.6.3 Scheduling: Video
2.6.3 Scheduling: Video
50
2.6.5 Time versus Processors: Video
2.6.5 Time versus Processors: Video
51
2.7.1 Partial Orders: Video
2.7.1 Partial Orders: Video
52
2.7.3 Representing Partial Orders As Subset Relations: Video
2.7.3 Representing Partial Orders As Subset Relations: Video
53
2.7.4 Equivalence Relations: Video
2.7.4 Equivalence Relations: Video
54
2.8.1 Degree: Video
2.8.1 Degree: Video
55
2.8.3 Isomorphism: Video
2.8.3 Isomorphism: Video
56
2.9.1 Coloring: Video
2.9.1 Coloring: Video
57
2.9.3 Connectivity: Video
2.9.3 Connectivity: Video
58
2.9.4 k-Connectivity: Video
2.9.4 k-Connectivity: Video
59
2.10.1 Trees: Video
2.10.1 Trees: Video
60
2.10.3 Tree Coloring: Video
2.10.3 Tree Coloring: Video
61
2.10.5 Spanning Trees: Video
2.10.5 Spanning Trees: Video
62
2.11.1 Stable Matching: Video
2.11.1 Stable Matching: Video
63
2.11.2 Matching Ritual: Video
2.11.2 Matching Ritual: Video
64
2.11.5 Optimal Stable Matching: Video
2.11.5 Optimal Stable Matching: Video
65
2.11.7 Bipartite Matching
2.11.7 Bipartite Matching
66
2.11.9 Hall's Theorem
2.11.9 Hall's Theorem
67
3.1.1 Arithmetic Sums: Video
3.1.1 Arithmetic Sums: Video
68
3.1.3 Geometric Sums: Video
3.1.3 Geometric Sums: Video
69
3.1.5 Book Stacking: Video
3.1.5 Book Stacking: Video
70
3.1.7 Integral Method: Video
3.1.7 Integral Method: Video
71
3.1.9 Stirling's Formula: Video
3.1.9 Stirling's Formula: Video
72
3.2.1 Asymptotic Notation: Video
3.2.1 Asymptotic Notation: Video
73
3.2.3 Asymptotic Properties: Video
3.2.3 Asymptotic Properties: Video
74
3.2.6 Asymptotic Blunders
3.2.6 Asymptotic Blunders
75
3.3.1 Sum And Product Rules: Video
3.3.1 Sum And Product Rules: Video
76
3.3.3 Counting with Bijections: Video
3.3.3 Counting with Bijections: Video
77
3.4.1 Generalized Counting Rules: Video
3.4.1 Generalized Counting Rules: Video
78
3.4.3 Two Pair Poker Hands: Video
3.4.3 Two Pair Poker Hands: Video
79
3.4.4 Binomial Theorem: Video
3.4.4 Binomial Theorem: Video
80
3.4.5 Multinomial Theorem: Video
3.4.5 Multinomial Theorem: Video
81
3.5.1 The Pigeonhole Principle: Video
3.5.1 The Pigeonhole Principle: Video
82
3.5.3 Inclusion-Exclusion Example: Video
3.5.3 Inclusion-Exclusion Example: Video
83
3.5.4 Inclusion-Exclusion 2 Sets: Video
3.5.4 Inclusion-Exclusion 2 Sets: Video
84
4.1.1 Tree Model: Video
4.1.1 Tree Model: Video
85
4.1.3 Simplified Monty Hall Tree: Video
4.1.3 Simplified Monty Hall Tree: Video
86
4.1.5 Sample Spaces: Video
4.1.5 Sample Spaces: Video
87
4.2.1 Conditional Probability Definitions: Video
4.2.1 Conditional Probability Definitions: Video
88
4.2.3 Law of Total Probability: Video
4.2.3 Law of Total Probability: Video
89
4.2.5 Bayes' Theorem: Video
4.2.5 Bayes' Theorem: Video
90
4.2.7 Monty Hall Problem: Video
4.2.7 Monty Hall Problem: Video
91
4.3.1 Independence: Video
4.3.1 Independence: Video
92
4.3.3 Mutual Independence: Video
4.3.3 Mutual Independence: Video
93
4.4.1 Bigger Number Game: Video
4.4.1 Bigger Number Game: Video
94
4.4.2 Random Variables: Independence: Video
4.4.2 Random Variables: Independence: Video
95
4.4.4 Random Variables: Uniform & Binomial: Video
4.4.4 Random Variables: Uniform & Binomial: Video
96
4.5.1 Expectation: Video
4.5.1 Expectation: Video
97
4.5.3 Expected Number Of Heads: Video
4.5.3 Expected Number Of Heads: Video
98
4.5.5 Total Expectation: Video
4.5.5 Total Expectation: Video
99
4.5.7 Mean Time to Failure: Video
4.5.7 Mean Time to Failure: Video
100
4.5.9 Linearity of Expectation: Video
4.5.9 Linearity of Expectation: Video
101
4.6.1 Deviation From The Mean: Video
4.6.1 Deviation From The Mean: Video
102
4.6.3 Markov Bounds: Video
4.6.3 Markov Bounds: Video
103
4.6.5 Chebyshev Bounds: Video
4.6.5 Chebyshev Bounds: Video
104
4.6.7 Variance: Video
4.6.7 Variance: Video
105
4.7.1 Law Of Large Numbers: Video
4.7.1 Law Of Large Numbers: Video
106
4.7.3 Independent Sampling Theorem: Video
4.7.3 Independent Sampling Theorem: Video
107
4.7.5 Birthday Matching: Video
4.7.5 Birthday Matching: Video
108
4.7.7 Sampling & Confidence: Video
4.7.7 Sampling & Confidence: Video
109
4.8.1 Random Walks: Video
4.8.1 Random Walks: Video
110
4.8.2 Stationary Distributions: Video
4.8.2 Stationary Distributions: Video
111
4.8.3 Page Rank: Video
4.8.3 Page Rank: Video