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

Sponsored by Abu Dhabi National Oil Company

4,636 already enrolled

Get in-depth knowledge of a subject
4.5

(157 reviews)

Beginner level

Recommended experience

2 months
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.5

(157 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

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Specialization - 5 course series

Introduction to R Programming for Data Science

Course 110 hours4.5 (533 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: Data Manipulation
Category: Data Analysis
Category: Statistical Programming
Category: R Programming
Category: Statistical Machine Learning
Category: Scripting Languages
Category: Data Processing
Category: Scripting
Category: Web Scraping
Category: Data Integration
Category: Computer Science
Category: Jupyter
Category: Algorithms
Category: Data Import/Export
Category: Software Development
Category: Computer Programming
Category: Extract, Transform, Load
Category: Data Structures
Category: Data Engineering

SQL for Data Science with R

Course 227 hours4.3 (164 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: Database Systems
Category: Relational Databases
Category: Database Management
Category: Database Development
Category: Query Languages
Category: SQL
Category: Database Management Systems
Category: Databases
Category: Database Architecture and Administration
Category: Database Theory
Category: Database Design
Category: Data Access
Category: Data Management
Category: Data Modeling
Category: Database Administration
Category: Data Architecture
Category: R Programming
Category: Data Analysis
Category: Data Manipulation
Category: Statistical Programming

Data Analysis with R

Course 316 hours4.7 (324 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 Analysis
Category: Data Science
Category: Statistical Analysis
Category: Statistics
Category: Analytics
Category: Statistical Methods
Category: Statistical Modeling
Category: Business Analytics
Category: Exploratory Data Analysis
Category: Predictive Modeling
Category: Mathematical Modeling
Category: Data Wrangling
Category: Regression Analysis
Category: Statistical Programming
Category: Correlation Analysis
Category: R Programming
Category: Predictive Analytics
Category: Data Transformation
Category: Tidyverse (R Package)
Category: Advanced Analytics

Data Visualization with R

Course 412 hours4.6 (250 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 Visualization
Category: Statistical Visualization
Category: Data Analysis
Category: Ggplot2
Category: Statistical Analysis
Category: Shiny (R Package)
Category: Data Visualization Software
Category: Data Presentation
Category: Leaflet (Software)
Category: Exploratory Data Analysis
Category: R Programming
Category: Plot (Graphics)
Category: Scatter Plots
Category: Rmarkdown
Category: Analytics
Category: Statistics
Category: Data Science
Category: Dashboard
Category: Data Storytelling
Category: Interactive Data Visualization

Data Science with R - Capstone Project

Course 524 hours4.5 (84 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: Statistical Analysis
Category: Data Analysis
Category: Analytics
Category: Data Science
Category: R Programming
Category: Data Wrangling
Category: Statistics
Category: Statistical Programming
Category: Statistical Methods
Category: Regression Analysis
Category: Statistical Modeling
Category: Shiny (R Package)
Category: Business Analytics
Category: Predictive Modeling
Category: Predictive Analytics
Category: Advanced Analytics
Category: Dashboard
Category: Exploratory Data Analysis
Category: Data Presentation
Category: Data Storytelling

Instructors

Rav Ahuja
IBM
53 Courses3,198,333 learners
Saishruthi Swaminathan
IBM
2 Courses323,900 learners

Offered by

IBM

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