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Certification

Certified Linear Algebra for Machine Learning & Generative AI

Show the world you have AI skills. Master essential linear algebra concepts powering machine learning and generative AI, and earn recognition for your expertise with this industry-focused certification.

Exam of 10 to 20 questionsCertificate for LinkedInBeginner · Intermediate
IT and development
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The exam

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Multiple-choice questions about the course. Pass with 70% or more and your certificate is issued at once, with a public page and an "Add to LinkedIn" button.

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What the exam covers

2 questions from each of the 15 chapters of the course

20 multiple-choice questions, drawn fresh for every attempt. Pass with 70% or more.

  1. 01Introduction and roadmap27:50
  2. 02Prerequisites and real numbers12:28
  3. 03Norms, distance and vector foundations23:04
  4. 04Vectors geometrically22:13
  5. 05Special vectors and applications24:50
  6. 06Vector operations and properties33:49
  7. 07Advanced vector concepts25:00
  8. 08Length and dot product30:46
  9. 09Cosine rule and Cauchy-Schwarz28:11
  10. 10Introduction to linear systems15:42
  11. 11Introduction to matrices16:09
  12. 12Core matrix operations40:39
  13. 13Gaussian elimination29:18
  14. 14Detailed example: solving systems15:47
  15. 15Augmented matrix, REF and RREF19:26
About the course

The Certified Linear Algebra for Machine Learning & Generative AI certification is designed for professionals seeking to master essential linear algebra concepts for advanced machine learning and AI applications. Gain skills that lead to increased productivity, improved decision-making, and a future-proof career in data science and artificial intelligence. Enroll now to unlock your full potential and gain a competitive advantage in this rapidly evolving field.

This certification covers the following topics:

  • Foundational Concepts
  • Coordinate Systems
  • Real Numbers and Vector Spaces
  • Vectors: Definition and Representation
  • Vector Operations: Addition, Subtraction, Scalar Multiplication
  • Linear Dependence and Independence
  • Norm (Magnitude or Length) and Euclidean Distance
  • Dot Product and its Geometric Interpretation
  • Linear Systems and Matrices
  • Matrix-Vector Multiplication in Machine Learning
  • Eigenvectors and Eigenvalues

Jobs this certification suits

Our AI checked this certification against 500 jobs; these get the most out of it. Each job links to its learning path.

Data Scientists