Prerequisites in place
Use norms, Euclidean distance and trigonometry on the Cartesian plane and the unit circle to solve vector problems.






























A three-hour course on vectors from the ground up. It begins with the prerequisites: norms and Euclidean distance, real numbers and vector spaces, the Cartesian coordinate system and the unit circle.
Then it covers vector definitions and operations, special vectors such as the zero vector and unit vectors, scalar multiplication and linear combinations, and ends on the dot product, projections, angles and the Cauchy-Schwarz Inequality.
Use norms, Euclidean distance and trigonometry on the Cartesian plane and the unit circle to solve vector problems.
Define vectors, carry out their basic operations, and recognize the zero vector and unit vectors and what makes them special.
Scale vectors and combine them into linear combinations, using them to manipulate and analyze vectors.
Calculate dot products, read them as projections and angles, and see what the Cauchy-Schwarz Inequality says about them.
See why prerequisites matter, then refresh norms and Euclidean distance, real numbers and vector spaces, and the Cartesian coordinate system and unit circle.
Learn what a vector is and its basic operations, meet special vectors such as the zero vector and unit vectors, and use scalar multiplication and linear combinations.
Discover the dot product and its geometric significance: how it relates to projections and angles, and what the Cauchy-Schwarz Inequality tells you.

Instructor · LUNARTECH
Tatev brings industry experience, advanced AI/ML degrees and a reputation as a thought leader in data science to LUNARTECH. She holds Bachelor’s and Master’s degrees in STEM, and her publications in top journals and presentations at international conferences showcase her expertise.
Refresh norms, Euclidean distance, the Cartesian system and the unit circle before you use them.
Define vectors, apply their operations, and combine them with scalar multiplication.
Use the dot product to relate vectors through projections and angles, and bound it with Cauchy-Schwarz.
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Every role uses all three modules. Here’s where each one leans hardest, and where its work ends up.
Represents records as vectors and compares them. Uses norms and distances to measure how alike they are.
Operations, Dot product
Data science
Reads model inputs as vectors in a space. Uses the dot product the way a model does.
Foundations, Operations, Dot product
Machine learning
Computes angles and projections for every object. Works on the Cartesian plane and the unit circle.
Foundations, Dot product
Computer graphics
Resolves a force into components with projections. Combines vectors to find a resultant.
Foundations, Operations, Dot product
Engineering
Represents records as vectors and compares them. Uses norms and distances to measure how alike they are.
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Updated November 2026.
Need help? These answers cover most of what people ask before they start.
The prerequisites: norms and Euclidean distance, real numbers and vector spaces, the Cartesian coordinate system and the unit circle.
No. It stays on vectors: their definition, operations, linear combinations and the dot product.
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Three hours from norms and distance through vector operations to the dot product and its geometry. Begin with a free lesson, or enroll in the full course.