Affiliated to National Board of Vocational Training Education, Government of India.
Affiliated to National Board of Vocational Training Education, Government of India.
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Machine Learning With R Training

22,900.00

Machine Learning with R Training, is designed to provide a holistic understanding of various ML algorithms with high-level theory and hands-on application of ML algorithms to classic data sets.

  • IBM® & IABAC® Certification
  • 5-Month | 350 Learning Hours
  • 100-Hour Live Online Training
  • 20 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

 

Machine Learning (ML) is a different approach where the computer learns the rules of solving complex problems without being explicitly programmed. Machine Learning algorithms are at the core and important pieces of data science.

Machine Learning with R Programing, is designed to provide a holistic understanding of various ML algorithms with high-level theory and hands-on application of ML algorithms to classic data sets.

Machine Learning With R Programming Course Module

  • R LanguageProgramming Basics
  • R language data Types
  • Structures and conditional statements
  • Introduction to R Studio
  • Data filtering and selecting
  • Data Mugging techniques in R
  • Basic Statistics and Exploratory Analysis
  • Descriptive summary statistics with Numpy
  • Summarize continuous and categorical data
  • Outlier analysis
  • Overview of Supervised and Unsupervised Machine Learning
  • Linear Regression
  • Clustering with K-means
  • Naive Bayes Classification
  • Introduction to Neural Networks
  • Advanced-Data Mugging
  • Outlier Analysis
  • Treating for missing values
  • Normalization vs Standardization of data
  • Supervised Machine Learning algorithms
  • K-Nearest Neighbors (KNN) concept and application
  • Naive Bayes concept and application
  • Logistic Regression concept and application
  • Classification Trees concept and application
  • Unsupervised Machine Learning algorithms
  • Clustering with K-means concept and application
  • Hierarchical Clustering concept and application
  • Setting up the project with ML workflow.
  • Data Preprocessing and statistical exploration
  • Building, Training, and evaluation of Machine Learning Model
  • Analysis of the case study: Property Estimations
  • Setting up the project with ML workflow.
  • Data Preprocessing and statistical exploration
  • Choosing the Machine Learning Algorithm for this case
  • Building, Training, and evaluation of Machine Learning Model

Machine Learning with R - Course Objectives

  • Introduce Machine Learning with a holistic approach.
  • Discuss the high-level theory of popular Machine Learning Algorithms
  • Hands-on coding of popular ML algorithms on classic data sets
  • Access the knowledge through the International Association of Business Analytics (IABAC™) framework.

Course Prerequisites

  • Introduce Machine Learning with a holistic approach.
  • Discuss the high-level theory of popular Machine Learning Algorithms
  • Hands-on coding of popular ML algorithms on classic data sets
  • Access the knowledge through the International Association of Business Analytics (IABAC™) framework.

Who should choose this course - Machine Learning with R?

This course is a foundation level course, so most of the aspiring Machine Learning candidates can opt for this course

  • Professionals aspiring to pursue a career in Machine Learning or Data Science in general
  • Fresh colleague graduates, who are looking for career options in Data Science
  • Senior professionals, who want to gain a solid foundation in Machine Learning to manage Data Science projects
  • Candidates pursuing Data Scientist tracks

Advantages of Machine Learning with R

This course provides a solid foundation in Machine Learning with R as the syllabus is aligned with international market requirements. As a part of the course, a certification assessment is conducted and candidates achieving a minimum qualifying scores receive a global certification, carrying immense value of the testimony of Python with Machine Learning knowledge.

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