B80 · English · shared course identity

B80 educator map · Mathematical Computing and Reproducible Experiments

A shared-identity planning surface for the English B80 reader: sequence, objectives, exercises with staged support, prerequisite routes, and laboratory bindings.

Open educator data · Open learner data

Boundary: this page organizes verified source metadata. It is not an execution service, automated grader, or claim that the native experiment receipts were rerun centrally.

Unit plan

Unit	Objectives	Previous	Exercises
Primer P01 - Running Python Experiments	Learning objectives	Start	Exercise 1 - values, types, and operators Exercise 2 - imports, calls, and help Exercise 3 - reading and fixing a traceback Exercise 4 - computation, display, and scripts Exercise 5 - clean kernels and hidden state
Control Flow, Collections, Functions, Modules, and Files	Learning objectives	`o002.p01`	Exercise 1 - collections and slices Exercise 2 - control flow before comprehensions Exercise 3 - functions, scope, and errors Exercise 4 - a learner module and red-green tests Exercise 5 - text, CSV, JSON, and a manifest
Computation, Representation, and Proof	Learning objectives	`o002.p02`	Exercise 1 - representation Exercise 2 - specifying tolerances Exercise 3 - the limits of an experiment Exercise 4 - a counterexample Exercise 5 - an experiment record
Objects, Values, and Functions	Learning objectives	`o002.u01`	Exercise 1 - choosing representations Exercise 2 - values and identity Exercise 3 - a function contract Exercise 4 - a dangerous alias Exercise 5 - tests and proof
Arrays, Shapes, and Vectorization	Learning objectives	`o002.u02`	Exercise 1 - shape and axis meanings Exercise 2 - vectorization and invariants Exercise 3 - a broadcasting contract Exercise 4 - tracing a view Exercise 5 - experiments are not general proofs
Visualization with Integrity	Learning objectives	`o002.u03`	Exercise 1 - question and encoding Exercise 2 - a truncated axis Exercise 3 - the meaning of error bars Exercise 4 - an accessible description Exercise 5 - figures and proof Mastery exercise - from data to plot to manifest
Exact and Symbolic Computation	Learning objectives	`o002.u04`	Exercise 1 - expressions and values Exercise 2 - a missing assumption Exercise 3 - equivalence and domains Exercise 4 - factors, roots, and checks Exercise 5 - stable symbolic artifacts Sage exercise 1 - parents, coercion, and factors Sage exercise 2 - exact solutions and approximations
Floating-Point Numbers, Error, and Stability	Learning objectives	`o002.u05`	Exercise 1 - `ulp` and the lost increment Exercise 2 - eliminating cancellation Exercise 3 - forward and backward error Exercise 4 - conditioning or algorithm? Exercise 5 - summation, tolerance, and limits on claims SciPy exercise - stability of `exprel`
Designing Experiments That Can Be Checked	Learning objectives	`o002.u06`	Exercise 1 - variables and confounders Exercise 2 - a seed is not a time machine Exercise 3 - selection and holdout Exercise 4 - effect size and stopping rules Exercise 5 - negative results and limits of evidence
Testing and Validating Computations	Learning objectives	`o002.u07`	Exercise 1 — choosing an assertion Exercise 2 — constructing an oracle Exercise 3 — metamorphic relations Exercise 4 — a boundary regression test Exercise 5 — the limits of testing evidence
Data, Configuration, and Provenance	Learning objectives	`o002.u08`	Exercise 1 — raw data, derived data, and lineage Exercise 2 — schemas and units Exercise 3 — configuration and safe paths Exercise 4 — rights and privacy Exercise 5 — semantics, bytes, and hashes
Automation and Reproducible Workflows	Learning objectives	`o002.u09`	Exercise 1 — task order Exercise 2 — a cycle Exercise 3 — timestamps Exercise 4 — a write failure Exercise 5 — a green workflow
Numerical Experiments and Their Prerequisites	Learning objectives	`o002.u10`	Exercise 1 - bisection invariants Exercise 2 - an iteration bound SciPy exercise - two implementations for a root of a cubic Exercise 3 - a quadrature check Exercise 4 - a residual is not a solution error Exercise 5 - an Euler experiment
A Verifiable Capstone Project	Learning objectives	`o002.u11`	Exercise 1 - classifying claims Exercise 2 - an incomplete manifest Exercise 3 - an unsafe path Exercise 4 - nonidentical reproduction Exercise 5 - responding to review

Laboratories

lab-o002-u04-plotting-m01 · plotting · unit o002.u04 · 1 exercise(s)
lab-o002-u05-sage · sagemath · unit o002.u05 · 2 exercise(s)
lab-o002-u06-scipy · scipy · unit o002.u06 · 1 exercise(s)
lab-o002-u11-scipy · scipy · unit o002.u11 · 1 exercise(s)

Prerequisite routes

A30/B80 core route: methods, bisection, SciPy, and sources of error · prerequisite A30 · core
B30 extension route: quadrature · prerequisite B30 · enrichment
B40 extension route: linear systems · prerequisite B40 · enrichment
B70 extension route: Euler steps · prerequisite B70 · enrichment