Practical Data Science with MATLAB Specialization

Practical Data Science with MATLAB Specialization

Practical Data Science with MATLAB Specialization Taught in English 22 languages available Some content may not be translated Instructors: Sam Jones +12 more Close Instructors Sam Jones MathWorks 4 Courses • 26,009 learners Cris LaPierre MathWorks 2 Courses • 42,542 learners Amanda Wang MathWorks 10 Courses • 31,873 learners Brian Buechel MathWorks 2 Courses •

Description

Practical Data Science with⁢ MATLAB ⁢Specialization is⁣ a cutting-edge program designed to provide individuals with the skills and knowledge needed to excel in the field of ‍data science. This online⁤ specialization, offered by one of the leading providers of technical computing ‌software,⁣ MATLAB, aims to equip learners with the practical skills and theoretical ⁢understanding necessary to tackle real-world ⁢data science challenges.

The ⁣specialization​ consists of a‌ series of courses that cover a wide range of ⁤topics, including data visualization, machine learning, data preprocessing, and predictive modeling. Each course is designed to help learners understand and apply ⁢fundamental data ​science concepts‌ using MATLAB, a powerful programming language and environment for technical computing.

One of the key advantages of the Practical Data Science ‌with MATLAB Specialization is its hands-on approach to ⁢learning. Through ⁢a ​combination of video lectures, ⁢interactive exercises

Practical Data Science with MATLAB Specialization

Taught in English

Some content may not be translated

Sam Jones
Cris LaPierre
Amanda  Wang

Instructors: Sam Jones

25,858 already enrolled

Included with Coursera Plus

Specialization – 4 course series

Get in-depth knowledge of a subject

4.8

(890 reviews)

Beginner level

Recommended experience

2 months at 4 hours a week
Flexible schedule
Learn at your own pace

What you’ll learn

  • Analyze large datasets & calculate statistics on specific groups in the data

  • Use interactive tools to investigate your data & remove noise and outliers

  • Create & evaluate machine learning models

  • Create reports & interactive documents to share your work

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