CS 101 · Year 1 · Semester 1 · 4 credits · Computer Science

Programming I (Python)

From first principles to reproducible actuarial pipelines: write clean, testable Python that prices risk.

Season 1 · 8 episodes

The Meridian Migration: Building an Actuarial Engine in Python

When a catastrophic spreadsheet error threatens Meridian Mutual with regulatory sanctions, a newly hired junior actuarial analyst must rebuild the firm's core pricing and valuation pipeline in pure, tested Python before the state insurance commission audit.

Protagonist · Maya Chen, Junior Actuarial Analyst at Meridian Mutual, equipped with solid actuarial theory but tasked with modernising a fragile legacy computing workflow.

Setting · The actuarial department of Meridian Mutual, a mid-sized regional life and casualty insurer racing against an eight-week regulatory audit deadline.

Stakes · A multi-million-dollar solvency discrepancy and a looming regulatory suspension of Meridian's flagship life insurance license if the rating engine cannot be proven transparent, reproducible, and mathematically flawless.

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Episodes

Season finale: Maya deploys a modular, fully tested, version-controlled Python premium calculation engine that passes the regulatory audit with zero defects and establishes the modern computational standard for Meridian Mutual.

From the lecturer: Welcome to CS 101. As an aspiring actuary or quantitative developer, Python is not just a scripting utility; it is the production engine where mathematical models meet real-world policyholder data. To master this course, do not watch these films passively. Set up a split-screen workspace with your IDE (VS Code or JupyterLab) on one side and the lecture on the other. Always keep an engineering notebook on your desk: trace control flows, draw memory diagrams of data structures, and draft function signatures on paper before typing a single character. We build your programming foundations from day one using genuine insurance datasets—mortality cohorts, loss triangles, and policy ledgers. Although this course does not map to a single preliminary SOA or CAS multiple-choice exam, it directly constructs the technical foundation required for modern Predictive Analytics (SOA Exam PA), Advanced Topics in Predictive Analytics (ATPA), and CAS Modern Actuarial Statistics (MAS-I and MAS-II), as well as real-world capital and pricing automation. Code along with every derivation, break the code deliberately to observe tracebacks, and test every function you write.

Cold open

At 7:42 AM on Maya's third day at Meridian Mutual, Chief Actuary Marcus Vance slams a 400-megabyte spreadsheet onto her screen. A nested IF formula across row 14,000 has misclassified tobacco users as preferred non-smokers, underpricing 12,000 term policies by 3.4 million dollars.

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Transcript

Master Python core syntax, primitive types, and variable assignments for actuarial modeling
Implement branching logic and iterative loops to process policyholder records
Define modular, reusable functions with docstrings and type annotations to price insurance contracts
Compute expected loss and pure premium programmatically across diverse risk profiles