• 09899714317

Benefits of the course

  • Fundamentals: Learn the basics and applications of data science.
  • R Programming: Master data manipulation and analysis using R.
  • Data Visualization: Create effective data visualizations with R tools.
  • Data Cleaning: Handle missing data and data inconsistencies.
  • Statistics: Understand essential statistical concepts for analysis.
  • EDA: Explore data patterns and trends with EDA techniques.
  • Machine Learning: Implement regression, classification, and clustering using R.
  • Model Evaluation: Assess and fine-tune machine learning models.
  • Feature Engineering: Optimize models with feature selection and creation.
  • Big Data: Handle large datasets with R and SparkR.
  • Practical Projects: Apply skills to real-world data science projects.
  • Ethics: Consider ethical and privacy implications in data science.
  • Tools: Familiarize yourself with essential R packages and RStudio.
  • Communication: Effectively communicate data insights to diverse audiences.
  • Project Management: Learn project management for data science initiatives.

Topics for this course

32 Lessons 216 hours


What is Data Science
Application of Statistics and Programming in Data Science
Importance of Data in Al, Data Science and Data Analytics


R Programming

DA with R

Predictive Analysis

Machine Learning

Natural Language Processing(NLP)

Target Audience

  • Data analysts and statisticians
  • R programmers seeking data science skills
  • Aspiring data scientists
  • R programmers seeking data science skills
  • Students and recent graduates
  • Business analysts
  • Entrepreneurs and start-up founders
  • Researchers and scientists
  • Data enthusiasts and hobbyists
  • Industry professionals (e.g., healthcare, finance, marketing)
  • Non-technical managers and decision-makers

  • Duration 216 hours
  • Lessons32
  • Skill levelIntermediate
  • CategoryData Science

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