關於此 專項課程

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Do you find yourself in an industry or field that increasingly uses data to answer questions? Are you working with an overwhelming amount of data and need to make sense of it? Do you want to avoid becoming a full-time software developer or statistician to do meaningful tasks with your data? Completing this specialization will give you the skills and confidence you need to achieve practical results in Data Science quickly. Being able to visualize, analyze, and model data are some of the most in-demand career skills from fields ranging from healthcare, to the auto industry, to tech startups. This specialization assumes you have domain expertise in a technical field and some exposure to computational tools, such as spreadsheets. To be successful in completing the courses, you should have some background in basic statistics (histograms, averages, standard deviation, curve fitting, interpolation). Throughout this specialization, you will be using MATLAB. MATLAB is the go-to choice for millions of people working in engineering and science, and provides the capabilities you need to accomplish your data science tasks. You will be provided with free access to MATLAB for the duration of the specialization to complete your work.
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100% 在線課程
立即開始,按照自己的計劃學習。
靈活的計劃
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初級
完成時間大約為4 個月
建議 4 小時/週
英語(English)
字幕:英語(English)
可分享的證書
完成後獲得證書
100% 在線課程
立即開始,按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
初級
完成時間大約為4 個月
建議 4 小時/週
英語(English)
字幕:英語(English)

此專項課程包含 4 門課程

課程1

課程 1

Exploratory Data Analysis with MATLAB

4.8
429 個評分
129 條評論
課程2

課程 2

Data Processing and Feature Engineering with MATLAB

4.6
169 個評分
59 條評論
課程3

課程 3

Predictive Modeling and Machine Learning with MATLAB

課程4

課程 4

Data Science Project: MATLAB for the Real World

提供方

MathWorks 徽標

MathWorks

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  • Yes. A free license is available to learners enrolled in the course. You must have a computer capable of running MATLAB. You can view the system requirements here.

  • You will be able to:

    • Import data from a variety of sources into MATLAB
    • Create compelling visualizations
    • Analyze and calculate statistics on groups of data
    • Perform common data cleaning techniques
    • Identify and create new features for machine learning models
    • Apply common machine learning methods and evaluate their performance
  • It is recommended that you take the courses in order. The skills gained in course one is considered pre-requiste knowledge for course two.

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