Learn how to use machine learning, with a focus on regression and classification, to automatically identify patterns in your data and make better predictions.
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What you need before starting this Foundations of Data Science: Prediction and Machine Learning course:
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This course is designed for absolute beginners. No prior knowledge needed.
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Everything you need to know about this online course, from duration to certification
One of the principal responsibilities of a data scientist is to make reliable predictions based on data. When the amount of data available is enormous, it helps if some of the analysis can be automated. Machine learning is a way of identifying patterns in data and using them to automatically make predictions or decisions. In this data science course, you will learn basic concepts and elements of machine learning.The two main methods of machine learning you will focus on are regression and classification. Regression is used when you seek to predict a numerical quantity. Classification is used when you try to predict a category (e.g., given information about a financial transaction, predict whether it is fraudulent or legitimate).For regression, you will learn how to measure the correlation between two variables and compute a best-fit line for making predictions when the underlying relationship is linear. The course will also teach you how to quantify the uncertainty in your prediction using the bootstrap method. These techniques will be motivated by a wide range of examples. For classification, you will learn the k-nearest neighbor classification algorithm, learn how to measure the effectiveness of your classifier, and apply it to real-world tasks including medical diagnoses and predicting genres of movies. The course will highlight the assumptions underlying the techniques, and will provide ways to assess whether those assumptions are good. It will also point out pitfalls that lead to overly optimistic or inaccurate predictions.
Difficulty Level
Introductory
Suitable for motivated learners
Subject Category
Computer Science, Data Analysis & Statistics
Part of our Computer Science, Data Analysis & Statistics curriculum
Course Language
English
All materials in English
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Investment around $99
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