Linear Algebra: Engineering the Future
"From aspiring data scientists to analysts tackling high-dimensional challenges — your journey starts here."
Taught byM Sanjeeva ReddyM.Sc. MathematicsWhat you'll learn
Learners will use eigen-analysis to rank web pages, study quantum stability, validate engineering vibrations, and apply it to extract biological markers, detect hidden text topics, spot cyber-attacks, and compress 3D assets.
Course content
3 modules11 lessons3h 06m
COMPRESS REALITY WITH PCA4 lessons · 1h 06m
- PRINCIPAL COMPONENT ANALYSIS (The Engine of AI)
- 01Linear algebra video 1
- COVARIANCE MATRIX (Mapping the Data Cloud)
- 02Linear algebra video 2
- TOP-k EIGENVECTORS (Selecting the Strongest Signals)
- 03Linear algebra video 3
- RECONSTRUCT FACES (Coding the Eigen-Face)
- 04Linear algebra video 4
QUANTUM – GOOGLE – DRONES3 lessons · 49 min
- QUANTUM STATE STABILITY (The Energy Eigen-States)
- 05Linear algebra video 5
- PAGERANK ITERATION (Surfing the Billion-Dollar Matrix)
- 06Linear Algebra video 6
- VIBRATION MODES (Drone Arm Stability Check)
- 07Linear Algebra video 7
GENES – WORDS – CYBER – MESH4 lessons · 1h 11m
- GENE-EXPRESSION PCA (Finding the Principal Genes)
- 08Linear Algebra video 8
- WORD-CO-OCCURRENCE PCA (Hidden Topics in News)
- 09Linear Algebra video 9
- CYBER-INTRUSION DETECTION (The Eigen-Gap Anomaly)
- 10Linear Algebra video 10
- EIGEN-SURFACE COMPRESSION (Optimizing 3D Meshes)
- 11Linear Algebra video 11
About this course
Course Outcomes:
- Implement PCA and SVD from scratch using Python/NumPy.
- Compress images and reduce dataset dimensions efficiently.
- The math behind Covariance Matrices and Eigen decomposition.
- The geometry of Orthogonal Projection and Basis Changes.
- The connection between Eigenvalues, Singular Values, and Variance.
Your teacher
M Sanjeeva Reddy
M.Sc. MathematicsFuture-ready mathematics innovator, blending AI, machine learning, and timeless principles to make math accessible and empowering.
