Index
Contents¶
Computer Science¶
10301 Machine Learning¶
| Name | Link | Summary |
|---|---|---|
| Background | 00 Background | Prerequisites: math and stats foundations underlying ML |
| Intro | 01 Intro | ML problem formulation (Task, Performance, Experience); supervised learning routine |
| Decision Trees | 02 Decision Trees | Tree-based classifiers; splitting criteria; overfitting |
| KNN | 03 KNN | K-Nearest Neighbors; distance metrics; choosing k |
| Perceptron | 04 Perceptron | Linear classifier; weight updates; convergence |
| Linear Regression | 05 Linear Regression | Least squares; closed-form solution; gradient descent |
| Logistic Regression | 06 Logistic Regression | Probabilistic classification; sigmoid; MLE |
| Model Selection | 07 Model Selection | Cross-validation; bias-variance tradeoff; hyperparameter tuning |
| Regularization | 08 Regularization | L1/L2 penalties; ridge and lasso; preventing overfitting |
| Neural Networks | 09 Neural Networks | Feedforward networks; backpropagation; activation functions |
| Learning Theory | 10 Learning Theory | PAC learning; sample complexity; generalization bounds |
| Societal Impacts | 11 Societal Impacts | Fairness, bias, ethics, and societal implications of ML |
| Deep Learning | 12 Deep Learning | CNNs, RNNs, deep architectures, training techniques |
| Reinforcement Learning | 13 Reinforcement Learning | Rewards, policies, Q-learning from an ML perspective |
| Dimensionality Reduction | 14 Dimensionality Reduction | PCA; feature compression; variance preservation |
| K-Means | 15 K-Means | Unsupervised clustering; centroid updates; convergence |
| Ensemble Methods | 16 Ensemble Methods | Bagging, boosting, random forests; combining weak learners |
| Recommender Systems | 17 Recommender Systems | Collaborative filtering; matrix factorization; user-item models |
15213 Computer Systems¶
| Name | Link | Summary |
|---|---|---|
| Course Overview | 01 Course Overview | Intro to systems thinking; why low-level knowledge matters |
| Computer Arithmetic | 02 Computer Arithmetic | Integer vs float representation; overflow; bit manipulation |
| Machine Level Programming | 03 Machine Level Programming | x86-64 assembly; registers; control flow; stack frames |
| Linking | 04 Linking | Static and dynamic linking; symbol resolution; relocation |
| Code Optimization | 05 Code Optimization | Compiler optimizations; loop unrolling; memory access patterns |
| Memory Hierarchy | 06 Memory Hierarchy | Registers, cache, RAM, disk; locality principles |
| Cache Memories | 07 Cache Memories | Cache organization; hit/miss; direct-mapped vs set-associative |
| Virtual Memory | 08 Virtual Memory | Address spaces; page tables; TLB; memory protection |
| Dynamic Memory Allocation | 09 Dynamic Memory Allocation | malloc/free; heap management; fragmentation |
| Processes and Multitasking | 10 Processes and Multitasking | Process model; context switching; fork and exec |
| Exceptional Control Flow | 11 Exceptional Control Flow | Interrupts; signals; exceptions; system calls |
| System-Level IO | 12 System-Level IO | Unix I/O; file descriptors; buffering |
| Network Programming | 13 Network Programming | Sockets; TCP/IP; client-server model |
| Concurrent Programming | 14 Concurrent Programming | Threads; synchronization; deadlock; semaphores |
| Chinese Reference | chi | Chinese-language summary of course concepts |
| English Reference | eng | English-language reference summary |
15281 Artificial Intelligence¶
| Name | Link | Summary |
|---|---|---|
| Search | 01-Search | Uninformed and informed search; BFS, DFS, A*; heuristics |
| Constraint Satisfaction Problems | 02-Constraint Satisfaction Problems | CSP formulation; backtracking; arc consistency; MRV heuristic |
| Linear and Integer Programming | 03-Linear and Integer Programming | LP formulation; vertex enumeration; Simplex; branch and bound for IPs |
| Propositional Logic and Logical Agents | 04-Propositional Logic and Logical Agents | KB, entailment, CNF, resolution, forward chaining, DPLL, SATPlan, fluents |
| Classical Planning | 05-Classical Planning | State-space graphs; GraphPlan; mutex relations; planning graph expansion |
| Markov Decision Process | 06-Markov Decision Process | MDP formulation; Bellman equations; value iteration; policy iteration |
| Reinforcement Learning | 07-Reinforcement Learning | TD learning; Q-learning; ε-greedy; approximate Q-learning with feature weights |
| Probability | 08-Probability | Conditional probability; Bayes' theorem; chain rule; marginalization; independence |
| Bayes Nets | 09-Bayes Nets | Graphical models; d-separation; variable elimination; prior/rejection/LW/Gibbs sampling |
| HMMs and Particle Filters | 10-HMMs and Particle Filters | Hidden Markov Models; forward-backward algorithm; particle filtering |
| Game Theory | 11-Game Theory | Normal/extensive form; Nash equilibrium; MSNE; Stackelberg; social choice |
17313 Software Engineering¶
| Name | Link | Summary |
|---|---|---|
| Introduction | 01 Introduction | Software engineering failures (Vasa, CrowdStrike); requirements; QA; DevOps |
| Software Archaeology | 02 Software Archaeology | Reading and understanding legacy codebases |
| Case Study | 03 Case Study | Real-world SE case analysis |
| Metrics and Measurement | 04 Metrics and Measurement | Code quality metrics; measuring complexity and coverage |
| Process: Milestones, Estimation, Planning | 05 Process - Milestones, Estimation, Planning | Software process models; effort estimation; project planning |
| Software Teams and Communication | 06 Software Teams and Communication | Team structures; communication patterns; coordination |
| Design Docs | 07 Design Docs | Writing technical design documents; RFCs; spec structure |
| Integrating AI into Products | 08 Integrating AI into Products | Engineering challenges when shipping AI/ML features |
| Intro to Software Architecture | 09 Intro to Software Architecture | Architectural styles; quality attributes; design decisions |
| Architecture: Modularity & Microservices | 10 Architecture - Modularity & Microservices | Modular design; microservices tradeoffs; service decomposition |
| Code Review Risk | 11 Code Review Risk | Risk-based code review; prioritizing reviews; defect prediction |
| Software Analysis Tools | 12 Software Analysis Tools | Static analysis; linters; formal verification tools |
| AIML, Dynamic Analysis, OSS, Dependencies | 14-21 AIML, Dynamic Analysis, OSS, Dependencies | AI/ML in SE; dynamic analysis; open source; dependency management |
Information Systems¶
67250 Information Systems Milieux¶
| Name | Link | Summary |
|---|---|---|
| Information Systems in the Digital Age | 01 Information Systems in the Digital Age | What IS is; types of systems (POS, ERP, etc.); sociotechnical effects |
| The Enterprise Strategy and Business Process Layers | 02 The Enterprise Strategy and Business Process Layers | Business strategy alignment with IS; process modeling and workflows |
| The Enterprise Application Layer | 03 The Enterprise Application Layer | Enterprise applications (ERP, CRM, SCM); software integration |
| The Enterprise Information and Infrastructure Layers | 04 The Enterprise Information and Infrastructure Layers | Data management; cloud; infrastructure supporting enterprise IS |
| Information Systems in the Enterprise and Beyond | 05 Information Systems in the Enterprise and Beyond | IS at organizational and societal scale; digital transformation |
67265 Design Fundamentals¶
| Name | Link | Summary |
|---|---|---|
| Design Fundamentals | 67265 Design Fundamentals | Core design principles: visual hierarchy, typography, layout, UX fundamentals |
67272 Application Design and Development¶
| Name | Link | Summary |
|---|---|---|
| Getting Started | 00 Getting Started | Rails setup; git workflow; generating models and scaffolding |
| Use Cases | 01 Use Cases | Use case modeling; actors; requirements documentation |
| MVC Pattern | 02 MVC Pattern | Model-View-Controller architecture; separation of concerns |
| Ruby | 03 Ruby | Ruby syntax; data types; OOP; blocks and iterators |
| Rails | 04 Rails | Rails conventions; routing; migrations; ActiveRecord basics |
| Relationships and Scopes | 05 Relationships and Scopes | has_many, belongs_to, has_many :through; named scopes |
| Testing Relationships and Scopes | 06 Testing Relationships and Scopes | RSpec/Minitest for model associations and scopes |
| Validations and Testing | 07 Validations and Testing | ActiveRecord validations; testing valid/invalid states |
| Callbacks and Testing | 08 Callbacks and Testing | before/after callbacks; testing side effects |
| Views and Controllers | 09 Views and Controllers | ERB templates; controller actions; params; redirects |
| Regular Expressions | 10 Regular Expressions | Regex syntax; matching and capturing; use in validations |
| Authentication | 11 Authentication | User sessions; password hashing; devise or custom auth |
| Authorization | 12 Authorization | Role-based access control; cancancan; restricting actions |
| Ruby Object Model | 13 Ruby Object Model | Modules; mixins; method lookup chain; metaprogramming basics |
| Refactoring | 14 Refactoring | Code smells; extract method; DRY principles in Rails |
| API | 15 API | Building RESTful APIs in Rails; JSON responses; versioning |
| Adding Search | 16 Adding Search | Search implementation; filtering; Ransack or custom queries |
| Testing Controllers and Views | 17 Testing Controllers and Views | Integration and controller tests; view testing |
| React | 18 React | Integrating React with Rails; components; props and state |
| Design | 19 Design | UI/UX design in the context of Rails apps |
| Data Visualization and Quality | 20 Data Visualization and Data Quality | Charting libraries; data cleaning; quality assurance |
| Deployment | 21 Deployment | Deploying Rails to Heroku or similar; environment config |
| Phase 2 | Phase 2 | Project phase 2 notes and requirements |
| Phase 3 | Phase 3 | Project phase 3 notes and requirements |
| Questions | Questions | Running list of questions from coursework |
| Solved | Solved | Reference of solved problems and debugging notes |
| Review | review | Exam or quiz review material |
67364 Practical Data Science¶
| Name | Link | Summary |
|---|---|---|
| Introduction | 00 Introduction | Course overview; data science workflow; tools |
| Exploratory Data Analysis | 01 Exploratory Data Analysis | Summary statistics; distributions; visualizations; detecting anomalies |
| Machine Learning | 02 Machine Learning | Applied ML pipelines; feature engineering; model evaluation |
| Big Data | 03 Big Data | Distributed computing; Spark; handling large-scale datasets |
67373 Consulting Project¶
| Name | Link | Summary |
|---|---|---|
| Consulting Models | 01 Consulting Models | Frameworks for structuring consulting engagements; MECE; issue trees |
| Client Context & Problem Analysis | 02 Client Context & Problem Analysis | Scoping a client problem; stakeholder analysis; hypothesis-driven approach |
Philosophy & Psychology¶
80100 Intro to Philosophy¶
| Name | Link | Summary |
|---|---|---|
| Linguistics | Linguistics | Philosophy of language; meaning, reference, and how words relate to the world |
| Metaphysics | Metaphysics | Nature of reality and existence; ontology; identity and persistence |
80226 Philosophy of Science¶
| Name | Link | Summary |
|---|---|---|
| Kuhn — Scientific Revolutions | 01-Kuhn-Scientific-Revolutions | Paradigm, normal science, anomalies, crisis, revolution; incommensurability; theory-ladenness |
| Greek Astronomy & Aristotle | 02-Greek-Astronomy-and-Aristotle | Saving the appearances; instrumentalism vs realism; teleology vs mechanism; four causes |
| Ptolemy & Copernicus | 03-Ptolemy-and-Copernicus | Mathematical models vs reality; heliocentric revolution; conceptual dissatisfaction as driver of change |
| Tycho, Kepler, Galileo | 04-Tycho-Kepler-Galileo | Empirical challenge to metaphysics; abandoning perfect circles; mathematization of nature |
| Galilean Mechanics & Newton I | 05-Galilean-Mechanics-Newton-I | Inertia; qualitative to mathematical explanation; law-governed nature |
| Newton II & Anomalies | 06-Newton-II-and-Anomalies | Universal gravitation; action at a distance; predictive power without full explanation; anomalies in successful theories |
| Pre-Darwin Natural History | 07-Pre-Darwin-Natural-History | Cuvier's catastrophism; Lamarck's evolution; species fixity challenged |
| Darwin, Natural Selection & Evolution | 08-Darwin-Natural-Selection-and-Evolution | Catastrophism vs uniformitarianism; Hutton, Lyell; Darwin's argument structure; philosophical significance |
| Course Notes | Philosophy of Science Notes | Consolidated notes across all lectures |
80261 Epistemology¶
| Name | Link | Summary |
|---|---|---|
| Course Intro | 00 | Course setup; readings list; intro to knowledge and justification |
| Overview | 01 Overview | What epistemology is; justified true belief; philosophical vs scientific approaches |
| Empiricism | 02 Empiricism | Knowledge from sensory experience; Hume; tabula rasa |
| Rationalism | 03 Rationalism | Knowledge from reason; innate ideas; Descartes |
| Locke | 05 Locke | Locke's empiricist theory of knowledge; primary/secondary qualities |
| Locke vs. Leibniz | 06 Locke vs. Leibniz | Debate between empiricism and rationalism on the source of ideas |
| Hypotheses about Unobservables | 11 Hypotheses about Unobservables | Scientific realism; how we reason about things we cannot directly observe |
| Wesley Salmon on Scientific Realism | [[20 Wesley Salmon's Argument on Scientific Realism and Molecular Reality]] | Salmon's argument for molecular reality; inference to the best explanation |
| Laws in Social Science | 21 Laws in Social Science - Dealing with Multiple Causation in Complex Phenomena | Causal complexity in social science; why universal laws are hard to establish |
| Sandra D. Mitchell | 22 Through the Fractured Looking Glass - Sandra D. Mitchell | Integrative pluralism; science doesn't yield simple universal laws |
| Summary | Summary | Course summary of key epistemological positions and arguments |
80335 Social and Political Philosophy¶
| Name | Link | Summary |
|---|---|---|
| Mill — On Liberty | 01 Mill - On Liberty | Harm principle; individual liberty; freedom of speech; tyranny of the majority |
| Berlin — Two Concepts of Liberty | 02 Berlin - Two Concepts of Liberty | Negative liberty (freedom from) vs positive liberty (freedom to) |
| Waldron — Homelessness | 03 Waldron - Homelessness | Property rights and homelessness; freedom and access to public space |
| Pettit — Republican Freedom | 04 Pettit - The Republican Ideal of Freedom | Republican freedom as non-domination; critique of negative liberty |
| Hesse — Black Fugitivity | 05 Hesse - Western Hegemony, Black Fugitivity | Race and political freedom; Black fugitivity as resistance to Western hegemony |
| Nozick — Anarchy, State & Utopia | 06 Nozick - Anarchy, State and Utopia | Libertarianism; minimal state; entitlement theory of justice |
| Cohen — Assessing Nozick | 07 Cohen - Assessing Nozick's Libertarianism | Critique of Nozick; self-ownership; limits of libertarian theory |
| Rawls — Theory of Justice | 08 Rawls - Theory of Justice | Original position; veil of ignorance; difference principle; justice as fairness |
| Harsanyi — Utilitarian Response to Rawls | 09 Harsanyi - A Utilitarian Response to Rawls | Utilitarian critique of Rawls; average vs maximin utility |
| Marxism | 10 Marxism | Class struggle; alienation; historical materialism; critique of capitalism |
| Anderson — Against Luck Egalitarianism | 11 Anderson - Against Luck Egalitarianism | Critique of luck egalitarianism; democratic equality as an alternative |
| Lebron — Relational Egalitarianism & Race | 12 Lebron - Relational Egalitarianism & Race | Race and relational equality; structural racism and political philosophy |
| McKinnon — Epistemic Injustice | 13 McKinnon - Epistemic Injustice | Testimonial and hermeneutical injustice; Miranda Fricker's framework |
| Young — Responsibility and Global Justice | Young - Responsibility and Global Justice - A Social Connection Model | Social connection model; structural injustice; global responsibility |
| 当代西方政治哲学的八大流派 | 当代西方政治哲学的八大流派 | Chinese-language overview of eight schools of contemporary Western political philosophy |
85413 Perception¶
| Name | Link | Summary |
|---|---|---|
| Introduction | 00 Introduction | What perception is; physical input to neural signal; perception-action loop |
| Introduction to Methods | 01 Introduction to Methods | Psychophysics; signal detection theory; measuring perceptual thresholds |
| Vision | 02 Vision | Visual system anatomy; light processing; object and depth perception |