A certificate course on "Data Analytics using R" can be a great way to introduce students and professionals to the power of R for data analysis. Here's an overview of what such a course might cover, along with details on eligibility.

1. Introduction to R
   • Overview of R and RStudio
   • Installation and setup
   • Basic syntax and operations
   • Data types and structures (vectors, lists, data frames, matrices)
2. Data Import and Export
   • Reading data from various sources (CSV, Excel, databases)
   • Writing data to files
   • Handling missing data
3. Data Manipulation
   • Using dplyr and tidyr for data manipulation
   • Filtering, selecting, and transforming data
   • Summarizing and grouping data
4. Common Classification Algorithms
   • Decision Trees
   • Random Forest
   • Support Vector Machines (SVM)
   • K-Nearest Neighbors (KNN)
   • Naive Bayes
5. Data Visualization
   • Introduction to ggplot2
   • Creating basic plots (histograms, scatter plots, box plots)
   • Customizing plots (themes, labels, annotations)
   • Advanced visualization techniques
   • Regression analysis (linear and logistic regression)
6. Data Cleaning and Preprocessing
   • Data normalization and transformation
   • Encoding categorical variables
7. Advanced Topics
   • Clustering techniques
   • K – means Algorithm
   • Hierarchical Algorithm
8. Tools and Packages
   • Introduction to popular R packages (caret, shiny, plotly)

The course is typically designed for:

1. Students :
• Undergraduate or graduate students in fields such as computer science, statistics, engineering, business, economics, or any related discipline.
• Basic knowledge of mathematics and statistics is recommended but not mandatory.
2. Professionals:
• Data analysts, statisticians, business analysts, or anyone looking to enhance their data analysis skills.
• Professionals from non-technical backgrounds seeking to transition into data analytics roles.
3. Researchers and Academics:
• Researchers who want to leverage R for statistical analysis in their projects.
• Academics interested in incorporating R into their curriculum or research methodology.

10 /+12 from any recognized board including NIOS, or any degree with a pass with 50% in the qualifying exams.