R for Analytics – Advanced

Track: Associate Enterprise Data Analyst (AEDA)
In R for Analytics—Advanced, students will practice wrangling text, date and numerical data and reporting these results. Students will become competent at a suite of tools in R and other popular R packages to accelerate and augment their data analysis workflow.

Flexible And Powerful Tool For Statisticians And Data Miners

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R for Analytics—Advanced introduces tools from the tidyverse and other packages to prepare numerical date and text data for analysis, import JSON files and report results from their data analysis in R Markdown and Shiny. In R for Analytics—Advanced, students will practice wrangling text, date and numerical data and reporting these results. Students will become competent at a suite of tools in R and other popular R packages to accelerate and augment their data analysis workflow.

Learning outcome:

Upon completion, participants should be able to demonstrate each of the following;
  1. Ability to load, clean, prepare and manipulate data
  2. Learn how to connect to relational database using R
  3. Design and solve advanced data-driven problems

Who should attend:

Analysts and business professionals who want to jumpstart their abilities in analysing data

3 days of in depth learning

Face to face with experienced Data Scientist.

Course Methodology

This course will utilize a combination of Lecture and Labs.

CADS Certification​

Earn certification upon completion.

Pre-requisite:
R for Analytics—Basics
Minimum Qualification:
Undergraduate Degree

Training Track

Associate Enterprise Data Analyst (AEDA)

R for Analytics – Advanced is one of the modules under our Associate Enterprise Data Analyst (AEDA) programme. AEDA is a 15-day training program that provides analysts with the tools required for efficient Data Analysis.

Details of Subject

Day 1 & 2
  1. Advanced Data Preparation (11.0 hrs) –  Participants will become familiar with tools for data preparation from the tidyverse set of packages, including tools for importing data, data wrangling, data tidying, string manipulation and date/time operations. Participants will be able to use a wider array of functions to prepare data into a format amenable to data analysis in R.
  2. Reporting in R Markdown (3.0 hrs) –  Participants will be introduced to the R Markdown document format, the backbone for an ecosystem for document authoring, which allows for the creation of reproducible data analysis reports in PDF, HTML and Word formats, as well as (time permitting) HTML5 slides. Participants will be acquainted with a time-saving data analysis workflow that allows analysts to easily create reproducible and convenient data analysis reports in formats that stakeholders are familiar with.
Day 3
  1. SQL with R / RSQLite (2.0 hrs) –  Participants will learn to set up SQL connections, queries, and write data frames to tables from R. Participants will be able to interact with large datasets stored in SQL databases directly in R, allowing for quicker data analysis while using less resources relative to reading data all at once.
  2. R Shiny (5.0 hrs) –  Participants will learn to work with the components of R Shiny, a package for creating web applications in R. Participants will be able to create and publish interactive dashboards to present data for stakeholders.

Lead Instructor

Narjes Khatoon Naseri
Narjes is a data scientist and a software engineer with more than 5 years of experience in data analysis and building predictive models. Her expertise covers exploratory data analysis, statistical modeling, machine learning and heuristic search algorithms. Narjes is also a professional trainer and content developer in Data Science domain. She specializes in conducting a complete lifecycle of Natural Processing Language (NLP) on social media and customer service systems for predicting society behavior, feedback classification and summarization. Narjes is also an expert in applying mathematical and artificial intelligence approaches to optimize planning and timetabling systems.

CADS Certification

AEDA CADS Certified R for Analytics

As one of the world’s top data science tools, R provides a robust environment for tabulating, analysing and visualising data. Demonstrate your mastery of the programming language that has become a powerhouse for business intelligence and big data analytics. This certification entails familiarity with different data types and their operation, connecting relational databases through R and results reporting in Markdown and Shiny.

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R for Analytics – Advanced