Simulate, understand, & visualize data like a data scientist

Course details

Data science is quickly becoming one of the most important skills in industry, academia, marketing, and science. Most data-science courses teach analysis methods, but there are many methods; which method do you use for which data? The answer to that question comes from understanding data. That is the focus of this course.

What you will learn in this course:

You will learn how to generate data from the most commonly used data categories for statistics, machine learning, classification, and clustering, using models, equations, and parameters. This includes distributions, time series, images, clusters, and more. You will also learn how to visualize data in 1D, 2D, and 3D.

All videos come with MATLAB and Python code for you to learn from and adapt!

This course is for you if you are an aspiring or established:

• Data scientist
• Statistician
• Computer scientist (MATLAB and/or Python)
• Signal processor or image processor
• Biologist
• Engineer
• Student
• Curious independent learner!

What you get in this course:

• >4 hours of video lectures that include explanations, pictures, and diagrams
• pdf readers with important notes and explanations
• Exercises and their solutions
• MATLAB code and Python code

With >3000 lines of MATLAB and Python code, this course is also a great way to improve your programming skills, particularly in the context of data analysis, statistics, and machine learning.

Why I am qualified to teach this course:

My research and teaching involve evaluating, validating, extending, and developing novel data analysis methods for large-scale, multivariate and multidimensional datasets in neuroscience (brain science). Data generation, parameterization, and visualization are the most important skills in neuroscience data analysis methods, and I have >15 years of experience working on this topic, teaching this topic, and writing technical books on this topic (look them up on amazon!).

So what are you waiting for??

Watch the course introductory video to learn more about the contents of this course and about my teaching style. If you are unsure if this course is right for you and want to learn more, feel free to contact with me questions before you sign up.

I hope to see you soon in the course!

Mike