INTRODUCTION TO R FOR DATA SCIENCE AND DATA ANALYTICS

Dear all,

We are pleased to announce our forthcoming event with the following details:

Theme: Introduction to R for Data Science and Data Analytics

Dates: Thursday, 1st June - Saturday, 3rd June, 2023

Duration: 2:00pm - 5:00pm (West African Time - WAT)

To register, use the link below:

https://forms.gle/whAGjhVJDM6vp5qU7

Contents:

DAY ONE
Time: 2pm-3pm
Module 1: Introduction to R and RStudio
- Overview of R and its applications in data science and data analytics
- Installing R and RStudio
- Understanding the RStudio interface
- Basic R syntax and data types
- Working with variables and basic arithmetic operations
Time: 3pm-4pm
Module 2: Data Manipulation with R
- Importing data into R from different file formats (e.g., CSV, Excel)
- Exploring and understanding data structures in R (vectors, matrices, data frames)
- Data cleaning and preprocessing techniques (handling missing values, data transformations)
Time: 4pm-5pm
Module 3: Exploratory Data Analysis (EDA) with R
- Introduction to descriptive statistics and visualization
- Generating summary statistics (mean, median, standard deviation, etc.)
- Creating basic data visualizations using ggplot2 package
DAY TWO
Time: 2pm-3pm
Module 4: Statistical Analysis with R
- Introduction to statistical concepts in R (hypothesis testing, confidence intervals)
- Conducting t-tests and chi-square tests for categorical data
- Performing linear regression analysis to model relationships between variables
Time: 3pm-4pm
Module 5: Data Visualization with R
- Advanced data visualization using ggplot2 package
- Customizing plots (colors, labels, themes)
- Creating complex visualizations such as bar plots, histograms, box plots, and heatmaps
Time: 4pm-5pm
Module 6: Introduction to Machine Learning with R
- Overview of machine learning concepts and algorithms
- Supervised learning: classification and regression
- Unsupervised learning: clustering and dimensionality reduction
DAY THREE
Time: 2pm-3pm
Module 7: Data Wrangling and Transformation
- Advanced data manipulation techniques using dplyr and tidyr packages
- Aggregating and summarizing data
- Reshaping data from wide to long format and vice versa
Time: 3pm-4pm
Module 8: Introduction to Big Data Analytics with R
- Overview of big data concepts and challenges
- Introduction to parallel computing and distributed systems
- Working with big data using R packages (e.g., dplyr, data.table)
Time: 4pm-5pm
Module 9: Data Science Project Workflow
- Understanding the end-to-end data science project lifecycle
- Formulating a data problem and defining project objectives
- Data acquisition and preparation
- Exploratory data analysis and feature engineering
Extras(To be given as a project or assignment)
Module 10: Case Studies and Practical Applications
- Applying R in real-world data science and data analytics scenarios
- Case studies across various domains (e.g., finance, healthcare, marketing)
- Solving practical problems using R and relevant packages
- Presenting and interpreting results effectively.

Kindly NOTE that these 3-day classes are 100% FREE!!! All you need is your system and available internet service.

Looking forward to seeing you all ….

Thank you.