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Under construction. This area is a framework being built: most courses have no teaching material yet, and things may change or break. Private self-study. Not an official programme and not recognised by any ministry or school. No qualification, mark or document is issued, and “years 1 to 3” and “advanced” are names of study paths only.

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B04 Linear algebra I: computation & geometry

Years 1 to 3 pathB: Years 1 to 3 coreplannedabout 120 h (planning estimate)

Draft lectures and exercises are available for this course. They were written by AI and checked by a second AI; no person has reviewed them yet. Use them as a study aid, not as an authority.

Study this course (draft)

Named in: Years 1 to 3 pathway

Why this course

Computational and geometric linear algebra: the working toolkit for gradients, least squares and later abstract theory.

Prerequisites

Required
F01 Algebra, functions & mathematical fluency
Recommended
none
Can be taken at the same time
none
Courses that require this one
B06, B07, B08, B10, B12, E07, E09, E10, E43

Concept-level units

Units follow the syllabus order, as a recommended sequence rather than a gate.

  1. Linear systems
  2. Matrices and transformations
  3. Span and independence
  4. Bases and dimension
  5. Determinants
  6. Eigenvectors and orthogonality

Assessable outcome

Move between a linear transformation, its matrix, and its geometric action.

Assessment design

  • topic exercises
  • mixed problem sets
  • unseen proof or derivation problems
  • cumulative examination

cumulative; uses spaced retrieval

Resources

Every title here is candidate, unverified unless marked verified. Titles were suggested while planning. Nobody has checked that they exist, what they cost or how they are licensed.

  • Strang · Introduction to Linear Algebra
  • MIT 18.06

Content record

Version
0.0.0
Review
no review of any kind
Provenance
catalogue imported from the owner brief of 29 Oct 2026; no teaching content authored
Known issues
none recorded
Type
course

Bridges and laboratories

  • Laboratory: Linear maps, span, projections, eigenvectors, SVD planned Preserve the relation between the geometric object and coordinates

You and this course

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