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R Programming for Data Science

Registration Fee


GH₵ 150.00

4 Weeks

Workshop Fee

GH₵ 1,500.00

About the Course

Dive into the world of data science with our beginner-friendly 4-week online workshop. In this comprehensive course, you'll unravel the basics of R, from data structures and manipulation to fundamental statistics. Best of all? You don’t need any prior programming experience!

Course Schedule

Our sessions are conveniently scheduled every Saturday, from 3-5 pm GMT (11 am-1 pm ET) and every Thursday, from 7-9 pm GMT (3-5 pm ET).

Embark on this transformative learning experience starting TBA. Don't miss out on unlocking the full potential of R programming!

Course Highlights:

  • 🖥️ Interactive and hands-on sessions: Get practical experience with real-world applications.

  • 🌍 Real-world applications: See how R applies to everyday data challenges.

  • 🤝 Weekly personalized assistance: Get your questions answered every week.

  • 🏆 Earn a completion certificate: Showcase your newly acquired skills.

What you will learn:

  • Introduction to R: Navigate RStudio and understand basic data types, vectors, and matrices.

  • Core Data Structures: Dive deep into lists, data frames, and factors.

  • Data Manipulation Mastery: Efficiently handle data using the 'dplyr' package.

  • Data Visualization: Harness the power of 'ggplot2' to craft compelling data visuals.

  • Statistics in R: From hypothesis testing to regression, explore R's robust statistical toolkit.

Who should attend?

  • Those at the start of their Machine Learning journey.

  • Budding Data Science enthusiasts.

  • Professionals keen on integrating R into their skillset.

  • Business Analysts pivoting to Machine Learning.

  • Anyone with a zest for Data Visualization and Analysis.

Your Instructor

Linda Amoafo

Linda, a Principal Data Scientist at Mogital Analytics, is also a doctoral candidate at the University of Utah, USA, in the Department of Population Health Sciences specializing in Biostatistics. Her groundbreaking research delves into analyzing multicollinearity among multiple exposures and refining causal inference within multi-stage modeling. With a robust academic foundation, Linda holds a Master's in Statistics from Northern Arizona University, USA, and a Bachelor's from Kwame Nkrumah University of Science and Technology, Ghana. Her expertise bridges Statistics, Data Science, and Biostatistics, making her a cross-disciplinary force in the field.

Linda Amoafo
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