PCA & multivariate signal processing, applied to neural data — 94% OFF Discount Coupon

Learn and apply cutting-edge data analysis techniques for "big neurodata" (theory and MATLAB/Python code)

★4.9 out of 5
6,552 students
Created by Mike X Cohen
English
Updated May 2026

Quick Facts — Course Summary

Here's a quick overview of everything you need to know about PCA & multivariate signal processing, applied to neural data before you enroll:

•Course Name: PCA & multivariate signal processing, applied to neural data
•Platform: Udemy
•Instructor: Mike X Cohen
•Coupon Last Verified: May 2, 2026
•Level: All Levels
•Topic: Teaching & Academics
•Subtopic: Linear Algebra
•Total Time: 17h 30m of video content
•Language: English
•Access Type: Unlimited lifetime access + updates
•Certificate: Included upon completion from Udemy
•Main Skills: Understand advanced linear algebra methods · Apply advanced linear algebra methods in MATLAB and Python · Analyzing multivariate time series datasets
•Requirements: Some linear algebra background (3+ hour crash course is provided) · Some neuroscience background (or interest in learning!)
•Current Price: $11.99 (was $199.99). You save $188.00 with 94% discount.
•How to Apply: Click the coupon button to activate your discount automatically
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Tip:For best results, apply the coupon in a regular browser window rather than incognito/private mode.

Skills You'll Master

By the end of PCA & multivariate signal processing, applied to neural data, you'll have these practical skills:

✓Understand advanced linear algebra methods .
✓Apply advanced linear algebra methods in MATLAB and Python .
✓Analyzing multivariate time series datasets .
✓Learn about modern neuroscience data analysis .
✓Includes a 3+ hour "crash course" on linear algebra .
✓Simulate multivariate data for testing analysis methods .
✓Appreciate the challenges neuroscientists are struggling with!.

What You Need Before Starting

Before enrolling in PCA & multivariate signal processing, applied to neural data, make sure you have:

•Some linear algebra background (3+ hour crash course is provided)
•Some neuroscience background (or interest in learning!)
•Some MATLAB/Python programming experience (only to complete exercises)
•Interest in learning applied linear algebra

About This Udemy Course

The following is the full official course description for PCA & multivariate signal processing, applied to neural data as published on Udemy by instructor Mike X Cohen:

What is this course all about?

Neuroscience (brain science) is changing -- new brain-imaging technologies are allowing increasingly huge data sets, but analyzing the resulting Big Data is one of the biggest struggles in modern neuroscience (if don't believe me, ask a neuroscientist!).

The increases in the number of simultaneously recorded data channels allows new discoveries about spatiotemporal structure in the brain, but also presents new challenges for data analyses. Because data are stored in matrices, algorithms developed in linear algebra are extremely useful. 

The purpose of this course is to teach you some matrix-based data analysis methods in neural time series data, with a focus on multivariate dimensionality reduction and source-separation methods. This includes covariance matrices, principal components analysis (PCA), generalized eigendecomposition (even better than PCA!), and independent components analysis (ICA). The course is mathematically rigorous but is approachable to individuals with no formal mathematics background. The course comes with MATLAB and Python code (note that the videos show the MATLAB code and the Python code is a close match).

You should take this course if you are a...
  • neuroscience researcher who is looking for ways to analyze your multivariate data.
  • student who wants to be competitive for a neuroscience PhD or postdoc position.
  • non-neuroscientist who is interested in learning more about the big questions in modern brain science.
  • independent learner who wants to advance your linear algebra knowledge.
  • mathematician, engineer, or physicist who is curious about applied matrix decompositions in neuroscience.
  • person who wants to learn more about principal components analysis (PCA) and/or independent components analysis (ICA)
  • intrigued by the image that starts off the Course Preview and want to know what it means! (The answers are in this course!)

Unsure if this course is right for you?

I worked hard to make this course accessible to anyone with at least minimal linear algebra and programming background. But this course is not right for everyone. Check out the preview videos and feel free to contact me if you have any questions.

I look forward to seeing you in the course!

Is the PCA & multivariate signal processing, applied to neural data Coupon Worth It?

Expert review by Andrew Derek, Lead Course Analyst at CoursesWyn.•Last updated: May 2, 2026.

Based on analysis of the curriculum structure, student engagement metrics, and verified rating data, PCA & multivariate signal processing, applied to neural data is a high-value resource for learners seeking to build skills inTeaching & Academics. Taught by Mike X Cohen on Udemy, the 17h 30m course provides a structured progression from foundational concepts to advanced techniques— making it suitable for learners at all levels. The current coupon reduces the price by 94%, from $199.99 to $11.99, removing the primary financial barrier to enrollment.

✓What We Like (Pros)

  • Verified 94% price reduction makes this course accessible to learners on any budget.
  • Aggregate student rating of 4.9 out of 5 indicates high learner satisfaction.
  • Strong enrollment base with over 6,552 students demonstrates course popularity and trust.
  • Includes an official Udemy completion certificate and lifetime access to all future content updates.

!Keep in Mind (Cons)

The following limitations should be considered before enrolling in PCA & multivariate signal processing, applied to neural data:

  • The depth of Teaching & Academics coverage may be challenging for absolute beginners without the listed prerequisites.
  • Lifetime access is contingent on the continued operation of the Udemy platform.
  • Hands-on projects and quizzes require additional time investment beyond video watch time.
Final Verdict: Worth It
This course offers exceptional value with current pricing
✓

Course Rating Summary

PCA & multivariate signal processing, applied to neural data Course holds an aggregate rating of 4.9 out of 5 based on 6,552 student reviews on Udemy.

4.9
★★★★★
6,552 Verified Ratings
5 stars
75%
4 stars
15%
3 stars
6%
2 stars
2%
1 star
2%

* Rating distribution is approximated from the aggregate score. Sourced from Udemy.

Instructor Profile

The following section provides background information on Mike X Cohen, the instructor responsible for creating and maintaining PCA & multivariate signal processing, applied to neural data on Udemy.

PCA & multivariate signal processing, applied to neural data is taught by Mike X Cohen, a Udemy instructor specializing in Teaching & Academics. For the full instructor biography, professional credentials, and a complete list of their courses, visit the official instructor profile on Udemy.

•Instructor Name: Mike X Cohen
•Subject Area: Teaching & Academics
•Teaching Approach: Practical, project-based instruction focused on real-world application of Teaching & Academics skills.

Frequently Asked Questions

The following questions and answers cover the most common queries about PCA & multivariate signal processing, applied to neural data, its coupon code, pricing, and enrollment process.

About the Author

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Andrew Derek

Lead Course Analyst at CoursesWyn with 8+ years of experience evaluating online learning platforms. I've analyzed 500+ Udemy courses and helped thousands of learners choose the right courses for their career goals.

⭐4.8/5 Rating
✓Trusted by 10K+ Students

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