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  • Berkeley Global

Practical Statistics for Data Scientists Using R

COMPSCI X402.1

48901130
Delivery Options Online

Get a hands-on introduction to statistics for data science using the R programming language. You explore the foundations of statistics with a strong emphasis on constructing models from data. Topics include descriptive statistics, probability (including conditional probabilities and Bayes rule), multiple regression, multiway analysis of variance, and logistic regression. You also study statistical concepts, methods, tools for modeling multivariate systems, and the statistical foundations for machine and statistical learning applications for drawing reliable conclusions from real-world data. You also get a basic introduction to the R programming language and R tools for data exploration, modeling and presentation of results.

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Sections

Section 007

Mar 22, 2021 to May 26, 2021 Live Online

Course Fee(s)

Course Fee credit (2 units)

$995.00

Type Live Online

Access classroom-style interactive learning from anywhere in the world! Attend scheduled online sessions with your instructor and classmates in addition to completing your coursework.

Live Online format allows you to take classes from anywhere with an internet connection. Classroom sections will be taught in this format through Spring 2021. Learn more about this format.

Beginning August 15, 2020, you must have a Zoom account to participate.

Many schools are now accepting transfer credit for online coursework, including health and sciences programs. Check with your institution before enrolling.

Days

M, W

Time

6:30PM to 8:00PM Pacific Time

Dates

Mar 22, 2021 to May 26, 2021

Schedule and Location

View Details

Instructional Hours

30.00

Delivery Options

Online

Available for Credit

2 semester units

Instructors

  • Allan Miller

This course applies to the following programs:

Certificate Program in Data Science

Expand or collapse section

Programming

  • Introduction to R: Data Exploration and Visualization
  • Python for Data Analysis and Scientific Computing
  • Introduction to Data Science
  • Introduction to Data Science Using R

Machine Learning

  • Introduction to Machine Learning Using Python
  • Machine Learning and Deep Learning With Spark
  • Practical Machine Learning (With R)
  • Machine Learning With TensorFlow

Core Courses

  • Practical Statistics for Data Scientists Using R
  • Introduction to Big Data
  • Data Science Principles and Practice Using Python
  • Data Visualization

Electives

  • Introduction to Databases
  • Introduction to SQL

Learn More About this Program

Professional Program in Data Analysis

Expand or collapse section

Data Analysis Courses

  • Introduction to Data Analytics
  • Introduction to R: Data Exploration and Visualization
  • Python for Data Analysis and Scientific Computing
  • Data Analytics and Visualization
  • Practical Statistics for Data Scientists Using R

SAS Analytics Courses

Data Management Courses

  • Introduction to Databases
  • Introduction to SQL
  • Business Intelligence With SQL Server
  • Data Mining Using SQL

Learn More About this Program

Prerequisites

Knowledge of statistics as covered in a first-semester undergraduate course. Knowledge and experience using a programming language such as Java, C, BASIC, FORTRAN, or Ruby.

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Course Fee

COMPSCI X402.1 - 007 - Practical Statistics for Data Scientists Using R

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Allan Miller

Allan Miller is a veteran data scientist and educator. He is an active member of the San Francisco Bay Area R-language data science community, founding and current faculty in the UC Berkeley Extension Data Science program, and a member of the Extension Program's data science advisory board.

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