Detailed information about "Data Science: Practical Machine Learning"


Key info
Offered byJohns Hopkins University
Description

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation.

WHAT YOU WILL LEARN

  • Use the basic components of building and applying prediction functions
  • Understand concepts such as training and tests sets, overfitting, and error rates
  • Describe machine learning methods such as regression or classification trees
  • Explain the complete process of building prediction functions

Accredited byCoursera
URL https://www.coursera.org/learn/practical-machine-learning


Additional info
Provider typeacademic center
Typecourse is part of the specialization
Synchronous / asynchronousasynchronous online course
Type of deliveryblended (practical training and lecture)
Formonline
Length9 hours
LanguageEnglish
Dates availableanytime
CostFREE (without a certificate of completion) / 49 USD/month
Has certificateYES
Registration / Access controlYES
User feedback 
ID163



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