Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
6 Hour(s) 25 Minute(s)
Language
English
Taught by
Mike X Cohen
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
Course Overview
Learn how to simulate and visualize data for data science, statistics, and machine learning in MATLAB and Python
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:
>6 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 >4000 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.
What do you need to know before taking this course?
You need some experience with either Python or MATLAB programming. You don't need to be an expert coder, but if you are comfortable working with variables, for-loops, and basic plotting, then you already know enough to take this course!
Course Content
- 10 section(s)
- 46 lecture(s)
- Section 1 Introductions
- Section 2 Descriptive statistics and basic visualizations
- Section 3 Data distributions
- Section 4 Time series signals
- Section 5 Time series noise
- Section 6 Image signals
- Section 7 Image noise
- Section 8 Data clustering in space
- Section 9 Spatiotemporal structure using forward models
- Section 10 Bonus section
What You’ll Learn
- Understand different categories of data
- Generate various datasets and modify them with parameters
- Visualize data using a multitude of techniques
- Generate data from distributions, trigonometric functions, and images
- Understand forward models and how to use them to generate data
- Improve MATLAB and Python programming skills
Skills covered in this course
Reviews
-
LLudwig F.
This course motivates students to explore on their own and makes them curious to further deepen what they have learned.
-
CChristian Bernscherer
A well prepared course with comprehensive material included. Some problems are easy, some are really challenging, but they are never boring. Well done, Mike!
-
SSimone Agostinelli
I took the course with the expectations of having a deeper understanding of the data simulation. Therefore I honestly enjoyed the first 4 sections of the course. The remaining ones are focused on times series and signals which I had no interest in deepening, actually I had really had times going forward. For the future students meaning to take this course I advice them to take only the first sections if interested in statistical data simulation, the whole course if interested in times series and signals.
-
AAnand Khare
Good explanation of plotting and data visualization. The course also covers basic explanation of different types of data, distributions, signals along with how to plot and visualize them in MATLAB and PYTHON.
