Linear Algebra for Machine Learning and Data Science

• When will I have access to the lectures and assignments?

  Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

  • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

  • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

• What will I get if I subscribe to this Specialization?

  When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

• What is the refund policy?

  If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

• Is financial aid available?

  Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

• What is the difficulty of this course?

  This is a beginner-friendly course, aiming to teach the concepts covered with minimal background knowledge necessary. If you're familiar with the concepts of linear algebra, you'll find this course a good review for the next course in the specialization, Calculus for Machine Learning and Data Science.

• I’m not good at math, is this course still for me?

  Yes! We want to break down the barriers that hold people back from advancing their math skills. In this course, we flip the traditional mathematics pedagogy for teaching math, starting with the real world use-cases and working back to theory.

  Most people who are good at math simply have more practice doing math, and through that, more comfort with the mindset needed to be successful. This course is the perfect place to start or advance those fundamental skills, and build the mindset required to be good at math.

• What areas of mathematics will I learn in this course?

  Linear algebra (matrices, vectors, and their applications)

• Why is mathematics for machine learning and data science important?

  With out-of-the-box tools, it’s easier than ever to begin a career as a machine learning engineer or data scientist. But to advance deeper in your career, create efficient models, troubleshoot algorithms, and incorporate creative thinking, a deeper understanding of the mathematics behind the models is needed.

• Do I need to take the courses in a specific order?

  No. Most learners would benefit from taking courses one and two together, as they introduce concepts that build upon each other, but course three is independent from the other courses in this specialization.

• Will I earn university credit for completing the Specialization?

  No, this Specialization is not for college credit.

• Is this a standalone course or a Specialization?

  Linear Algebra for Machine Learning and Data Science can be taken as a standalone course or the first course in the Mathematics for Machine Learning and Data Science Specialization.

• Can I apply for financial aid?

  Yes, Coursera provides financial aid to learners who cannot afford the fee.

More questions? Visit the Learner Help Center.