Episodes
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Programming Languages Week 8 (Oct 26+29): Expressions, Assignment & Control Flow
Deep dive into expressions and statement-level control: how expressions are evaluated, assignment and type conversions, short-circuit evaluation, and the selection, loop, and jump statements that direct execution. Sources: Week 8 (Oct 26-29) – Sebesta §§7.2–7.8: Expressions and Assignment Week 8...
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ML Week 7 (Oct 26+28): Model Evaluation & Ensembles
Deep dive into model evaluation and ensemble methods: how to measure and improve models, and how bagging, random forests, boosting, and Bayesian additive regression trees combine weak learners into stronger ones. Sources: Week 7 (Oct 26-28) – ISLP Ch 8.2: Bagging, Random Forests, Boosting, BART...
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Programming Languages Test 2 Prep (Oct 22): Syntax, Analysis, Scope & Types
Test-prep deep dive for the closed-book Test 2: language implementation methods, BNF/EBNF syntax description, parse trees and ambiguity, operational semantics of assignment, lexical and syntax analysis, names, binding, scope and lifetime, plus pointer/reference types and type checking — built…
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TCA Class 13–14 (Oct 20+22): Soft Skills in the Post-AI Workplace
Soft skills in the post-AI workplace: what engineering students think soft-skills education is worth, how soft skills fit 21st-century project management, the NACE career-readiness competencies, and the human element in Industry 5.0 projects — plus the dark side of the digital workplace and the...
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Programming Languages Week 7 (Oct 19+22): Scope, Types & Functional Programming
A recap of binding, scope, and lifetime, then pointer and reference types plus how type checking works — closing with the fundamentals of functional programming, from mathematical functions to what makes a language functional. Sources: Week 7 (Oct 19-22) – Sebesta §§5.4–5.6: Binding, Scope,...
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ML Week 6 (Oct 19+21): Feature Engineering
Representing data so algorithms can learn from it: categorical variables and one-hot encoding, binning and scaling continuous features, and engineering new features that capture what matters. Sources: Week 6 (Oct 19-21) – Müller & Guido Ch. 4: Representing Data and Engineering Features
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Programming Languages Week 6 (Oct 12+15): Grammars, Parsing, and Scope
How compilers turn source code into structured logic: formal grammars and BNF/EBNF notation, parse trees and ambiguity, how lexical analysis breaks code into tokens, the parsing problem and recursive-descent parsing — plus names, variables, binding, scope, and referencing environments. Sources:...
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ML Weeks 1-4 (Sep 7-Oct 7): Exam Prep
A 49-minute deep-dive study guide for the October 14 closed-book ML exam, covering weeks 1–4: the ingredients of machine learning, statistical learning, logical tree-based models, probabilistic models (logistic regression, Naive Bayes), geometric models (k-nearest neighbors, support vector...
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PL Week 5 (Oct 5+8): From Source Code to Execution
How does source code become a running program? This episode follows the full pipeline: implementation methods — compilers, interpreters, and hybrids (1.7); describing syntax with grammars, parse trees, and ambiguity (3.1–3.2); the key ideas of lexical and syntax analysis (4.1); and what "meaning"...
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TCA Class 9–10 (Oct 6+8): Privacy Frameworks
Week 5 (Oct 5-11) – What Is GDPR Compliance? (Palo Alto Networks) Week 5 (Oct 5-11) – NIST Privacy Framework Getting Started
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Data Visualization Week 4 (Sep 28+30): Focus, Design & Storytelling
Week 4 (Sep 28-30) – Storytelling with Data, Ch. 4–7 (pp. 99–186)
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TCA Class 9–10 (Oct 6+8): AI Ethics Frameworks
EU AI Act — High-Level Summary (artificialintelligenceact.eu) AI Risk Management Framework — Palo Alto Networks
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TCA Class 9 (Oct 6): AI in Education
Computer Science Education in the Age of Generative AI — Russell Beale (arXiv:2507.02183) AI in Higher Education in Latin America — survey report
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ML Week 4 (Oct 5+7): Linear Regression
Sources: ISLP - James et al. An Introduction to Statistical Learning - Chapter 3
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