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Overview
Key Features
- Then we look through what vectors and matrices are and how to work with them, including the knotty problem of eigenvalues and eigenvectors, and how to use these to solve problems. Finally we look at how to use these to do fun things with datasets - like how to rotate images of faces and how to extract eigenvectors to look at how the Pagerank algorithm works.
- Since we're aiming at data-driven applications, we'll be implementing some of these ideas in code, not just on pencil and paper. Towards the end of the course, you'll write code blocks and encounter Jupyter notebooks in Python, but don't worry, these will be quite short, focussed on the concepts, and will guide you through if you’ve not coded before.
- At the end of this Mathematics for Machine Learning - Linear Algebra course offered by Coursera in partnership with Imperial College London, you will have an intuitive understanding of vectors and matrices that will help you bridge the gap into linear algebra problems, and how to apply these concepts to machine learning.
Programme Structure
Courses include:
- Linear Algebra and to Mathematics for Machine Learning
- Vectors are objects that move around space
- Matrices in Linear Algebra: Objects that operate on Vectors
- Matrices make linear mappings
- Eigenvalues and Eigenvectors: Application to Data Problems
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
- Self-paced
Campus Location
- Mountain View, United States
Disciplines
Mathematics Machine Learning View 207 other Short Courses in Machine Learning in United StatesWhat students do after studying
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- Beginner level
- No previous experience necessary
- To obtain additional information about the programme, we kindly suggest that you visit the programme website, where you can find further details and relevant resources.
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
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International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
Additional Details
- Audit: free access to course materials except graded items
- Certificate: a trusted way to showcase your skills
- A year of unlimited access with Coursera Plus $399
Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.
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