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Data Mining for Business Analytics & Data Analysis in Python

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Data Mining for Business Analytics & Data Analysis in Python Udemy Coupon

Data Mining for Business Analytics & Data Analysis in Python

Python for Data Analytics & Explainable Artificial Intelligence. Data Mining for Business Data Analytics & Intelligence.

Created by Diogo Alves de Resende | 9 hours on-demand video course

Are you looking to learn how to do Data Mining like a pro? Do you want to find actionable business insights using data science and analytics and explainable artificial intelligence? You have come to the right place. I will show you the most impactful Data Mining algorithms using Python that I have witnessed in my professional career to derive meaningful insights and interpret data.

In the age of endless spreadsheets, it is easy to feel overwhelmed with so much data. This is where Data Mining techniques come in. To swiftly analyze, find patterns, and deliver an outcome to you. For me, the Data Mining value added is that you stop the number crunching and pivot table creation, leaving time to come with actionable plans based on the insights.

What you’ll learn

  • Identify the value of data mining for quickly analyzing and interpreting data.
  • Apply data mining algorithms using Python programming language for Business Analytics.
  • Explain the principles behind various data mining algorithms, including supervised and unsupervised machine learning, and explainable AI
  • Explain the results of data mining models using explainable artificial intelligence models: LIME and SHAP.
  • Practice applying data mining techniques through hands-on exercises and case studies.
  • Implement cluster analysis, dimension reduction, and association rule learning using Python.
  • Perform survival analysis, Cox proportional hazard regression, and CHAID using Python.
  • Use random forest and feature selection to improve the accuracy of data mining models.
  • Develop a portfolio of data mining projects for Business Data Analytics and Intelligence.
  • Use data mining techniques to inform business decisions and strategies.

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