Self-Paced Analytics with R

OVERVIEW
Building Strategic Influence in Matrix Organizations

This is an online course that is structured for all those who are interested to work in the Analytics industry, and is also designed to further aid data analysts, business analysts, data engineers, data scientists, technical managers, and entrepreneurs looking to understand R programming concepts.

WHAT YOU'LL LEARN
Why you shouldn't miss this course

By the end of this course, participants will have the leadership toolkit to shape and steer GenAI portfolios across their organization.

PREREQUISITES
Recommended experience

CURRICULUM
Structured for
Strategic Application
  • What is Data Science? Understanding the 4 Vs.
  • What is Business Analytics?
  • Understanding the data and defining the scope of Business Analytics
  • What are Decision models?
  • Companies that use R
  • Role of a data scientist
  • History of R
  • About R and R Studio
  • Configuration required for R
  • Data Types of R
    Hands on – on R data types
    Simple Statistics using R
    Grouping, Loops, Conditional Execution
  • Importing data and connecting to database systems
  • Merging, concatenating, reshaping data
  • Using dplry package for data manipulation
  • Write Functions
  • Various types of visualization
  • Using ggplot package
  • Creating Graphs in R – Line plots, Bar charts, Pie charts, Histograms, density plots, Scatter plots
  • Why study statistics?
  • Applications and types of statistics
  • Population vs sample
  • Types of data and statistical variables
  • Summarize the data and making decisions using summary statistics
  • Random Variables, Expected Value
  • Probability Distribution
  • Standard Deviation and Variance
  • Types of Distributions
  • Understanding Normal Distribution
  • Skewness & Kurtosis
  • Types of Sampling
  • What is CLT and its application?
  • P-value, z score
  • T-Distribution and Poisson distribution
  • Null and Alternate hypothesis
  • Type I and Type II errors
  • Inference Statistics
    ANOVA
  • Linear Regression
  • Non-Linear Regression
    Trees
  • Text Analytics
  • Rattle
  • Forecasting
  • Moving Average/Holt Winter
  • ARIMA/ARMA
  • Use Case

RECOMMENDED PARTICIPANT SETUP
This course follows Cognixia's AI-first,
hands-on learning model

Access to sanitized process maps, KPI definitions, candidate initiative lists, and basic cost baselines (time, cycle time, error or rework rates)

INTERESTED IN THIS COURSE?
Let's Connect

Speak with a Cognixia specialist about enrollment options, custom cohorts for your leadership team, or tailored delivery formats for your organization.

Response within 1 business day
Available in 5 delivery formats globally
Volume pricing for teams of 10+
Get in touch

One of our specialists will contact you within one business day.

FAQs
Frequently
Asked Questions

Find details on duration, delivery formats, customization options, and post-program reinforcement.

Yes, the course completion certificate is provided once you successfully complete the training program. You will be evaluated on parameters such as attendance in sessions, an objective examination, and other factors. Based on your overall performance, you will be certified by Cognixia.

WHY COGNIXIA
Why Cognixia for This Course

KEEP EXPLORING
Mapped Official Learning
Leadership
Equip enterprise leaders to drive culture, skills, policy, and operating-model change required for sustainable Generative AI adoption at scale.
In-Person Workshop, Virtual Instructor-Led
Applied
Enterprise-grade security, governance, and Responsible AI controls to protect, govern, and operate GenAI and agentic systems safely at scale.
In-Person Workshop, Virtual Instructor-Led
Applied
Build portable, enterprise-grade GenAI systems that run consistently across Databricks, AWS, and Google Vertex AI—without vendor lock-in, quality drift, or governance gaps.
In-Person Workshop, Virtual Instructor-Led
Applied
Systematic testing, evaluation, and quality engineering frameworks for validating GenAI and agentic AI systems at enterprise scale.
In-Person Workshop, Virtual Instructor-Led
Applied
Production-grade GenAIOps and LLMOps practices to deploy, monitor, evaluate, and govern enterprise-scale LLM and agentic applications with reliability and control.
In-Person Workshop, Virtual Instructor-Led
Applied
Design, build, evaluate, and operate production-grade agentic AI systems with multi-agent orchestration, tool integration, and enterprise-grade safety controls.
In-Person Workshop, Virtual Instructor-Led

READY TO SHAPE YOUR AI FUTURE?
Let's build the workforce
of the future

Enroll your leadership cohort in Designing GenAI Use-Case Portfolios & Business Cases.
Custom cohorts available for enterprise teams.