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Data Science and Machine Learning Free Online Course at University California, Berkeley

Opportunities Circle is brining another great opportunity for you, Data Science and Machine Learning Free Online Course at University of California, Berkeley

It will help you with the basic concept of machine learning and data science

 

Here is some more details about the Data Science and Machine Learning Free Online Course.

About the course:

One of the main responsibilities of a data scientist is to make reliable predictions based on data. When the amount of data available is enormous, it is useful that part of the analysis can be automated. Machine learning is a way to identify patterns in data and use 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 machine learning methods that you will focus on are regression and classification. Regression is used when looking to predict a numerical quantity. Classification is used when you try to predict a category (for example, given information about a financial transaction, predict if it is fraudulent or legitimate).

For regression, you will learn how to measure the correlation between two variables and how to calculate a line of best fit to make 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.

Table of Contents

  • Country: Online
  • Financial coverage: Fully Funded
  • Eligible Regions: Anyone from any part of the world can apply for the course
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    Eligibility Criteria :

    Here are the eligibility criteria for the Data Science and Machine Learning Free Online Course

    • Anyone who is interested in this field can join the course.
    • This course is fundamental so you don’t need to be a programmer to learn this course.

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    Benefits :

    Here is what you will get in this course

    • Fundamental concepts of machine learning
    • Linear regression, correlation and regression phenomenon to the mean
    • Basic probability and Bayes theorem
    • Classification using the k nearest neighbors algorithm
    • How to Compare and Evaluate the Accuracy of Machine Learning Models

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    Application Process:

    Please follow the link below to apply for the program

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