IBM
Applied Data Science with R Specialization
IBM

Applied Data Science with R Specialization

Build Your Data Science Skills with R & SQL. Master the ability to transform data into information and insights.

Rav Ahuja
Saishruthi Swaminathan
Yan Luo

Instructors: Rav Ahuja

3,915 already enrolled

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Specialization - 5 course series

Get in-depth knowledge of a subject

4.5

(136 reviews)

Beginner level

Recommended experience

2 months at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Perform basic R programming tasks like working with data structures, data manipulation, using APIs, webscraping, and using R Studio and Jupyter.

  • Create relational databases and tables, load them with data from CSV files, and query data using SQL and R using JupyterLab.

  • Complete the data analysis process, including data preparation, statistical analysis, and predictive modeling.

  • Communicate data analysis findings with data visualization charts, plots, and dashboards using libraries such as ggplot, leaflet and R Shiny.

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Taught in English

Specialization - 5 course series

Get in-depth knowledge of a subject

4.5

(136 reviews)

Beginner level

Recommended experience

2 months at 10 hours a week
Flexible schedule
Learn at your own pace

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Specialization - 5 course series

Introduction to R Programming for Data Science

Course 110 hours4.5 (432 ratings)

What you'll learn

  • Manipulate primitive data types in the R programming language using RStudio or Jupyter Notebooks.

  • Control program flow with conditions and loops, write functions, perform character string operations, write regular expressions, handle errors.

  • Construct and manipulate R data structures, including vectors, factors, lists, and data frames.

  • Read, write, and save data files and scrape web pages using R.

Skills you'll gain

Category: Data Science
Category: Linear Regression
Category: Data Visualization
Category: R Programming
Category: Exploratory Data Analysis

SQL for Data Science with R

Course 227 hours4.3 (131 ratings)

What you'll learn

  • Create and access a database instance on the cloud

  • Compose and execute basic SQL statements - SELECT, INSERT, UPDATE, DELETE, CREATE, DROP

  • Construct SQL statements to filter, sort, group results, use built-in functions, compose nested queries, access multiple tables

  • Analyze data from Jupyter using R and SQL by combining SQL and R skills to query real-world datasets

Skills you'll gain

Category: Data Science
Category: R Programming

Data Analysis with R

Course 316 hours4.7 (275 ratings)

What you'll learn

  • Prepare data for analysis by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values.

  • Compare and contrast predictive models using simple linear, multiple linear, and polynomial regression methods.

  • Examine data using descriptive statistics, data grouping, analysis of variance (ANOVA), and correlation statistics.

  • Evaluate a model for overfitting and underfitting conditions and tune its performance using regularization and grid search.

Skills you'll gain

Category: Data Science
Category: Data Analysis
Category: Statistical Analysis
Category: Data Visualization
Category: R Programming

Data Visualization with R

Course 412 hours4.6 (211 ratings)

What you'll learn

  • Create bar charts, histograms, pie charts, scatter plots, line graphs, box plots, and maps using R and related packages.

  • Design customized charts and plots using annotations, axis titles, text labels, themes, and faceting.

  • Create maps using the Leaflet package for R.

  • Create interactive dashboards using the Shiny package for R.

Skills you'll gain

Category: Data Science
Category: Data Analysis
Category: Data Visualization
Category: R Programming

Data Science with R - Capstone Project

Course 524 hours4.6 (72 ratings)

What you'll learn

  • Write a web scraping program to extract data from an HTML file using HTTP requests and convert the data to a data frame.

  • Prepare data for modelling by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values.

  • Interpret datawithexploratory data analysis techniques by calculating descriptive statistics, graphing data, and generating correlation statistics.

  • Build a Shiny app containing a Leaflet map and an interactive dashboard then create a presentation on the project to share with your peers.

Skills you'll gain

Category: Data Science
Category: Data Analysis
Category: Select (Sql)
Category: Relational Databases (RDBMS)
Category: R Programming

Instructors

Rav Ahuja
IBM
52 Courses2,615,395 learners
Saishruthi Swaminathan
IBM
2 Courses295,588 learners

Offered by

IBM

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