Date Science with R Programming Online Course
(All course fees are in USD)
The Data Science with R programming Online Course covers data exploration, data visualization, predictive analytics, and descriptive analytics techniques with the R language. You will learn about R packages, how to import and export data in R, data structures in R, various statistical concepts, cluster analysis, and forecasting.
Offered in Partnership with
Total applied learning: 64 hours
- 60+ hours of blended learning
- 10 real-life industry projects
- Online virtual classes by industry experts
Skills to be Learned
- Business analytics
- R programming and its packages
- Data structures and data visualization
- Apply functions and DPLYR function
- Graphics in R for data visualization
- Hypothesis testing
- Apriori algorithm
- Kmeans and DBSCAN clustering
Award upon Successful Completion
Data Science with R Language Certification Training “Certificate of Achievement”
- Gain a foundational understanding of business analytics
- Learn how to install R, RStudio, workspace setup, and learn about the various R packages
- Master R programming and understand how various statements are executed in R
- Gain an in-depth understanding of data structure used in R and learn to import/export data in R
- Define, understand and use the various apply functions and DPLYR functions
- Understand and use the various graphics in R for data visualization
- Gain a basic understanding of various statistical concepts
- Understand and use the hypothesis testing method to drive business decisions
- Understand and use linear and non-linear regression models, and classification
techniques for data analysis
- Learn and use the various association rules with the Apriori algorithm
- Learn and use clustering methods including k-means, DBSCAN, and hierarchical clustering
Project 1 – Products rating prediction for Amazon
Help Amazon, a US-based e-commerce company, improve its recommendation engine by predicting ratings for the non-rated products and adding them to recommendations accordingly.
Project 2 – Demand Forecasting for Walmart
Predict accurate sales for 45 Walmart stores, considering the impact of promotional markdown events. Check if macroeconomic factors have an impact on sales.
Project 3 – Improving customer experience for Comcast
Provide Comcast, a US-based global telecom company, key recommendations to improve customer experience by identifying and improving problem areas that lower customer satisfaction.
Project 4 – Attrition Analysis for IBM
IBM, a leading US-based IT company, wants to identify the factors that influence employee attrition by building a logistics regression model that can help predict employee churn.
Who Should Enrol
We recommend this data science training particularly for:
- IT professionals
- Analytics professionals
- Software developers
- Anyone interested in R programming
Learners need to possess an undergraduate degree, a high school diploma, or senior high school students.
Lesson 0 – Course Introduction
Lesson 1 – Introduction to Business Analytics
Lesson 2 – Introduction to R Programming
Lesson 3 – Data Structures
Lesson 4 – Data Visualization
Lesson 5 – Statistics for Data Science-I
Lesson 6 – Statistics for Data Science-II
Lesson 7 – Regression Analysis
Lesson 8 – Classification
Lesson 9 – Clustering
Lesson 10 – Association
Accessible Period of Course
1 year from date of enrolment
Programmer Analyst III – Cardiology Information Systems at New York-Presbyterian Hospital
Level of granularity. Tutor knowledge. Class size. Tutor’s confidence, subject knowledge, and high level of commitment to student understanding of the material. Tutor assisted students who had issues with SAS installation. Great Tutor-Student interaction.
Member of the Network on Institutional Investors and Long-term Investment
Great experience with the provider, enjoyed learning, very helpful application, and staff support. Good start for mastering R, SAS, and Excel.
Head of Project Management
The course was delivered successfully. It was very punctual, organized, and thorough. Overall, it was good.
Senior Facility Manager at CBRE
My instructor is obviously a Pro at what she does. I wish I had someone around like her to mentor me when I was younger. Some of the technical aspects of the course are a little challenging, but the concepts for doing what is being taught is becoming clear to me. I hope this will make all the difference as I delve into the coursework even more.
The course helped me to improve my skill set and gain the confidence to handle the role of an analyst. I had a break in my career due to immigration policies and had utilized the time to learn new skills, which helped me get a new job faster.
*Note: We reserve the right to revise/change any of the course content &/or instructor at our sole & absolute discretion, without prior notice to learner.
- Students 1 student
- Max Students1000
- Duration64 hour
- Skill levelall
- Re-take course10000
Lesson 0 - Course Introduction
Lesson 1 - Introduction to Business Analytics
Lesson 2 - Introduction to R Programming
Lesson 3 - Data Structures
Lesson 4 - Data Visualization
Lesson 5 - Statistics for Data Science-I
Lesson 6 - Statistics for Data Science-II
Lesson 7 - Regression Analysis
Lesson 8 - Classification
Lesson 9 - Clustering
Lesson 10 - Association