(Preliminary schedule, subject to change) Date Topic Reading Assignment due Wed, Jan 19 Introduction and Motivation (book chapter) Fri, Jan 21 Git and Team Collaboration Mon, Jan 24 From Models to AI-Enabled Systems (book chapter) Building Intelligent Systems, Ch. 5, 7, 8 Wed, Jan 26 Model Quality 1: Accuracy and Correctness (book chapter 1, book chapter 2) Building Intelligent Systems, Ch. 19 I1: Case Study Teamwork Primer Fri, Jan 28 Stream processing: Apache Kafka Mon, Jan 31 Model Quality 2: Slicing, Capabilities, Invariants (book chapter) Behavioral Testing of NLP Models with CheckList Wed, Feb 02 Goals and Success Measures for AI-Enabled Systems Building Intelligent Systems, Ch. 2, 4 Fri, Feb 04 Measurement & unit testing Mon, Feb 07 Requirements and Risks 1 (short notes) The World and the Machine Wed, Feb 09 Requirements and Risks 2 Building Intelligent Systems, Ch. 6, 7, 24 M1: Modeling and First Deployment Fri, Feb 11 Requirements/Risk analysis Mon, Feb 14 Tradeoffs among Modeling Techniques (book chapter) Building Intelligent Systems, Ch. 18 Wed, Feb 16 Deploying a Model (book chapter 1, book chapter 2) Building Intelligent Systems, Ch. 13 and Exploring Development Patterns in Data Science Fri, Feb 18 Architecture Mon, Feb 21 Quality Assessment in Production (book chapter) Building Intelligent Systems, Ch. 14, 15 Wed, Feb 23 Data Quality (book chapter) Data Cascades in High-Stakes AI I2: Requirements and Architecture Fri, Feb 25 Continuous Integration: Jenkins Mon, Feb 28 Infrastructure Quality, Deployment, and Operations (book chapter 1, book chapter 2, book chapter 3) The ML Test Score Wed, Mar 02 Midterm Fri, Mar 04 Midsemester break & spring break Mon, Mar 14 Managing and Processing Large Datasets (book chapter) Business Systems with Machine Learning Wed, Mar 16 Process & Technical Debt (book chapter 1, book chapter 2) Hidden Technical Debt in Machine Learning Systems I3: Exploring Tools or PhD Project Fri, Mar 18 Containers: Docker Mon, Mar 21 Human AI Interaction Building Intelligent Systems, Ch. 8 and Guidelines for Human-AI Interaction Wed, Mar 23 Intro to Ethics + Fairness (book chapter) Algorithmic Accountability: A Primer Fri, Mar 25 Monitoring: Prometheus, Grafana Mon, Mar 28 Building Fairer AI-Enabled System 1 Improving Fairness in Machine Learning Systems Wed, Mar 30 Building Fairer AI-Enabled System 2 A Mulching Proposal M2: Infrastructure Quality Fri, Apr 01 Fairness Mon, Apr 04 Explainability & Interpretability (book chapter) Black boxes not required or Stop Explaining Black Box ML Models… Wed, Apr 06 Transparency and Accountability (book chapter) People + AI, Ch. Explainability and Trust Fri, Apr 08 Spring carnival, no classes Mon, Apr 11 Versioning, Provenance, and Reproducability (book chapter) Building Intelligent Systems, Ch. 21 & Goods: Organizing Google's Datasets Wed, Apr 13 Security and Privacy M3: Monitoring and CD Fri, Apr 15 Threat modeling Mon, Apr 18 Safety 1 Wed, Apr 20 Safety 2 I4: Fairness Fri, Apr 22 tbd. Mon, Apr 25 Fostering Interdisciplinary Teams Wed, Apr 27 Summary and Review M4: Security and Feedback Loops Mon, May 2, 1-4pm Final Project Presentations Final report
