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  • Introduction to Data Science Frank Kane -
    This course is really comprehensive. We'll start with a crash course in the Python programming language and a review of basic statistics and probability; but then we've got about 70 different topics to cover in data mining, AI and machine learning including Bayes Theorem, regressions, clustering techniques, experimental design, decision trees and much more; and we'll build real neural networks using Tensorflow and Keras.
    2 Lessons 00:08:26 Hours English Beginner
    R199.99
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  • Introduction to R Kirill Eremenko -
    Master the basics of data analysis by manipulating common data structures such as vectors, matrices, and data frames.
    10 Lessons 01:01:42 Hours English Beginner
    R199
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  • R Programming Advanced Kirill Eremenko -
    It's about learning those tools that are has for your disposal and actually knowing and learning how to apply them. And moreover practicing those application to have lots of different exercises. We're going to be analyzing whether trends we're going to be cleaning data we're going to be looking at different data on machine maintenance so lots of different projects from different worlds of analytics and they will allow us to see how to apply those advanced skills in the real world. And of course we're going to have lots of fun along the way.
    0 Lessons 00:00:00 Hours English Advanced
    R170 R199
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  • Data Science - R Regression Modelling Various Instuctors -
    Understanding regression modelling.
    3 Lessons 00:44:31 Hours English Advanced
    Free
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