R for Analytics – Basics

Track: Associate Enterprise Data Analyst (AEDA)
Topics covered in this module include: data types, data wrangling, control flow, and data visualisation. R is one of the most popular and user- friendly programming languages/environments, often a standard for business data analytics.

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R for Analytics—Basics is a 3-day module for fresh graduates and analysts with a goal to provide students with a basic introduction to R programming. Topics covered in this module include: data types, data wrangling, control flow, and data visualisation. R is one of the most popular and user-friendly programming languages/environments, often a standard for business data analytics.

Learning outcome:

Upon completion, participants should be able to demonstrate each of the following;
  1. Ability to handle various data types, structures, and statements
  2. Learn how to create and use functions, repeating functions
  3. Design and solve more advanced data related problems by writing workable programs using R packages

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.

Basic programming knowledge
Minimum Qualification:
Undergraduate Degree

Training Track

Associate Enterprise Data Analyst (AEDA)

R for Analytics – Basics 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
  1. Introduction to R Programming (7.0 hrs) –  Participants will learn the fundamentals of R programming, covering operators, data types and structures. Users will be able to choose appropriate data structures for various use cases, saving time. and Additionally they will learn to manipulate data in data structures and perform basic analysis with R.
Day 2
  1. Data Preparation (3.0 hrs) –  Topics covered include importing data, dealing with missing data and functions. Users will be able to transform data into a format which is more suitable for analysis. These methods can make analyses more credible.
  2. Control Structures and Functions (4.0 hrs) –  Participants will learn to write basic control structures, use the apply family of functions and define user-defined functions in R. Participants can reduce redundancy in their code, resulting in more readable code with less errors.
Day 3
  1. Data Visualization (7.0 hrs) –  Participants will be introduced to R graphics created with functions from base and ggplot2. R programming allows students to effectively visualize data for business insight.

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 – Basics