What will you learn in Data Science with R Programming Certification Training Course
Master R programming fundamentals, including data types, operators, and functions
Perform data extraction, cleaning, and wrangling using dplyr and tidyr
Apply statistical inference techniques to draw insights from data
Implement supervised and unsupervised machine learning algorithms (e.g., linear/logistic regression, decision trees, clustering)
Program Overview
Module 1: Introduction to Data Science with R
⏳ 1 hour
Topics: What is Data Science; lifecycle stages; big data, Hadoop, Spark; R setup
Hands-on: Install R/RStudio; import and explore sample datasets
Module 2: Statistical Inference
⏳ 45 minutes
Topics: Measures of center and spread; probability distributions; hypothesis testing
Hands-on: Compute summary statistics and conduct t-tests in R
Module 3: Data Extraction, Wrangling & Exploration
⏳ 1 hour
Topics: Data pipelines; handling CSV/JSON/XML; exploratory data analysis; visualization basics
Hands-on: Clean and reshape datasets; generate plots with ggplot2
Module 4: Introduction to Machine Learning
⏳ 45 minutes
Topics: ML workflow; linear and logistic regression implementation
Hands-on: Train and evaluate regression models on real datasets
Module 5: Classification Techniques
⏳ 1 hour
Topics: Decision trees; random forests; Naive Bayes; support vector machines
Hands-on: Build and compare classification models in R
Module 6: Unsupervised Learning & Clustering
⏳ 45 minutes
Topics: K-means, C-means, hierarchical clustering; cluster evaluation
Hands-on: Perform clustering and visualize groupings
Module 7: Recommender Engines
⏳ 45 minutes
Topics: Association rules; user- vs. item-based filtering; recommendation use cases
Hands-on: Create a recommendation system using R packages
Module 8: Text Mining
⏳ 45 minutes
Topics: Bag of Words; TF-IDF; sentiment analysis workflows
Hands-on: Extract and analyze text data from Twitter
Module 9: Time Series Analysis
⏳ 1 hour
Topics: Time series components; ARIMA and ETS models; forecasting techniques
Hands-on: Decompose and forecast time series datasets
Module 10: Deep Learning Basics
⏳ 1 hour
Topics: Neural network fundamentals; reinforcement learning overview
Hands-on: Build a simple ANN for classification
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Job Outlook
Median salary for experienced Data Scientists in the U.S.: $162,800 + $6,000 bonus
Data Science job openings are growing at over 30% annually
Roles include Data Scientist, Machine Learning Engineer, Data Analyst, Quantitative Analyst
Skills in R, machine learning, and statistical modeling are in high demand across tech, healthcare, finance, and retail
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Specification: Data Science with R Programming Certification Training Course
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FAQs
- Basic programming experience is helpful but not required.
- The course introduces R setup, syntax, and basic functions.
- Hands-on labs guide learners through data types and operators.
- Prior knowledge accelerates learning but beginners can follow along.
- Focus is on practical application rather than theory-heavy coding.
- Yes, includes linear/logistic regression, decision trees, and clustering.
- Teaches evaluation metrics for classification and regression models.
- Covers real datasets for hands-on ML exercises.
- Introduces recommender systems and association rules.
- Focuses on applying ML in data science workflows with R.
- Includes projects in media, healthcare, social media, and aviation domains.
- Hands-on exercises for data extraction, cleaning, visualization, and modeling.
- Projects help build a portfolio for job applications.
- Encourages end-to-end implementation from raw data to insights.
- Offers lifetime access to materials for practice after the course.
- Yes, includes ARIMA and ETS models for forecasting.
- Covers text mining with Bag of Words, TF-IDF, and sentiment analysis workflows.
- Hands-on exercises analyze datasets from social media and other sources.
- Prepares learners for both numeric and textual data analysis.
- Supports building predictive and analytical models in real-world scenarios.
- Data Scientist, Machine Learning Engineer, Data Analyst, Quantitative Analyst.
- Skills in R, machine learning, and statistical modeling are highly valued.
- Opportunities exist in tech, healthcare, finance, and retail.
- Certification strengthens resumes and portfolio projects.
- Median salary for experienced data scientists is approximately $162,800 in the U.S.
