Machine learning with R
Course Overview
Key Feature
Course outline
You will Learn
Prerequisites
Machine learning with R is very important course and this course is for those who want to see themselves as a future analyst the main aim of this Machine learning course or training is to familiarize you with supervised & unsupervised learning using R which is a programming language and also you get to know R language supports predictive modeling with Machine learning.
- 4 Days / 32 Hrs For Classroom or Online Training
- Soft copy of Study materials
- Course Completion Certificate
- Flexibility to choose classes
- Training by Certified World class trainer
- Industry wise – Real life practical examples
- Teaching assistance to support your learning journey
- Learn the required skills using Technocerts.
Machine Learning vs Statistical Modeling & Supervised vs Unsupervised Learning
- Machine Learning Languages, Types, and Examples
- Machine Learning vs Statistical Modelling
- Supervised vs Unsupervised Learning
- Supervised Learning Classification
- Unsupervised Learning
Supervised Learning I
- K-Nearest Neighbors
- Decision Trees
- Random Forests
- Reliability of Random Forests
- Advantages & Disadvantages of Decision Trees
Supervised Learning II
- Regression Algorithms
- Model Evaluation
- Model Evaluation: Overfitting & Underfitting
- Understanding Different Evaluation Models
Unsupervised Learning
- K-Means Clustering plus Advantages & Disadvantages
- Hierarchical Clustering plus Advantages & Disadvantages
- Measuring the Distances Between Clusters – Single Linkage Clustering
- Measuring the Distances Between Clusters – Algorithms for Hierarchy Clustering
- Density-Based Clustering
Dimensionality Reduction & Collaborative Filtering
- Dimensionality Reduction: Feature Extraction & Selection
- Collaborative Filtering & Its Challenges
There is an increasing demand for skilled data scientists across all industries, making this data science certification course well-suited for participants at all levels of experience. We recommend this Data Science training particularly for the following professionals:
- IT professionals looking for a career switch into data science and analytics
- Software developers looking for a career switch into data science and analytics
- Professionals working in data and business analytics
- Graduates looking to build a career in analytics and data science
- Anyone with a genuine interest in the data science field
- Experienced professionals who would like to harness data science in their fields
- Basic knowledge of mathematics is required especially linear algebra, calculus, probability, Matrices.
- Some basic knowledge of coding.
- At least high school level math skills will be required
