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Machine Learning with R

Live Online (VILT) & Classroom Corporate Training Course

R is a language that is most suited for ML programming and achieving mastery in it is paramount for a career in ML. Master ML with R and become part of the technology revolution that will shape the future world.

Expert-Led VILT & Classroom Hands-On CloudLabs Certification Voucher Available
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Overview

This course will help you learn all the concepts of R and ML along with Supervised vs Unsupervised Learning, the ways in which Statistical Modeling relates to Machine Learning, and a comparison of each using R libraries.

Objectives

At the end of Machine Learning with R training course, participants will

  • Understand the behavior of data as they build significant models
  • Learn about the various libraries offered by R to manipulate, preprocess and visualize data
  • Supervised, Unsupervised Machine Learning and relation of statistical modelling to machine learning
  • Learn to use optimization techniques to find the minimum error in your machine learning model
  • Learn various machine learning algorithms like KNN, Decision Trees, SVM, Clustering in detail
  • Implement algorithms and R libraries such as CRAN-R in real world scenarios
  • Learn the technique to reduce the number of variables using Feature Selection and Feature Extraction
  • Learn to use multiple learning algorithms to obtain better predictive performance

Prerequisites

Elementary programming knowledge. Familiarity with statistics

Course Outline

  • Statistical analysis concepts
  • Descriptive statistics
  • Introduction to probability and Bayes theorem
  • Probability distributions
  • Hypothesis testing & scores

  • Intro to R Programming
  • Installing and Loading Libraries
  • Data Structures in R
  • Control & Loop Statements in R
  • Functions in R
  • Loop Functions in R
  • String Manipulation & Regular Expression in R
  • Working with Data in R
  • Data Visualization in R
  • Case Study

  • Machine Learning Modelling Flow
  • Types of Machine Learning
  • Performance Measures
  • Bias-Variance Trade-Off
  • Overfitting & Underfitting
  • How to treat Data in ML

  • Maxima and Minima
  • Cost Function
  • Learning Rate
  • Optimization Techniques

  • Linear Regression
  • Case Study
  • Logistic Regression
  • Case Study
  • K-NN Classification
  • Case Study
  • Naive Bayesian classifiers
  • Case Study
  • SVM – Support Vector Machines
  • Case Study

  • Clustering approaches
  • K Means clustering
  • Hierarchical clustering
  • Case Study

  • Decision Trees
  • Case Study
  • Introduction to Ensemble Learning
  • Different Ensemble Learning Techniques
  • Bagging
  • Boosting
  • Random Forests
  • Case Study: Heterogeneous Ensemble Machine Learning
  • PCA (Principal Component Analysis) and Its Applications
  • Case Study: PCA/FA

  • Introduction to Recommendation Systems
  • Types of Recommendation Techniques
  • Collaborative Filtering
  • Content based Filtering
  • Hybrid RS
  • Performance measurement
  • Case Study

Available Training Modes

Pick the format that fits your team.

Same authorised curriculum, same trainers, same hands-on cloud labs — delivered the way that works for you.

Live Online (VILT)

Real-time instructor-led sessions over Zoom or Teams. Same classroom, different time zones.

Most popular

Classroom

Face-to-face training delivered at your office, our Bengaluru centre, or any partner venue worldwide.

Onsite

Self-Paced

Recorded sessions plus 24/7 access to cloud labs and assessments. Learn at the pace that works for each engineer.

On-demand

Blended

Live workshops with self-paced reinforcement and project-based labs. Best for hybrid teams across regions.

Hybrid teams
All modes include: hands-on cloud labs, recordings, assessments, certificate of completion. Talk to a solutions advisor →

Our Training Process

How a course becomes measurable skill.

One contract, five steps, zero handoffs. From discovery to deployment, the same Synergific team owns the outcome — not a chain of vendors.

5 Steps from your scoping call to certified, productive engineers.
01

Discover & set goals

We start with a scoping call to understand your team's current skill level, target outcomes, deadlines, and certification needs — then translate that into a measurable success plan with named owners on both sides.

02

Curate the right path

We map the optimal learning path — instructor-led, self-paced, or blended — with hands-on cloud labs, prerequisite refreshers, and certification vouchers built in. No filler modules, no padded curriculum.

03

Deliver hands-on training

Authorised trainers run live sessions backed by 24/7 cloud labs and real-world projects. Theory and practice on the same day — learners stop forgetting concepts before they get to apply them.

04

Assess & mentor

Continuous skill checks, mock exams, and 1:1 mentoring keep the program honest. If anyone falls behind, we course-correct in-flight — you'll never find out at the end that two engineers couldn't keep up.

05

Certify & apply on the job

Voucher-backed certification, post-training office hours, and 30-day reinforcement so skills land on real work — not just on the exam scorecard. Success measured after the course ends, not before.

Client Stories

What our clients say

Voices from L&D leaders, architects, and program managers who’ve trusted us with their upskilling.