This program is designed to equip statisticians with the necessary skills to leverage the power of R for advanced data analysis and machine learning tasks. In today's data-driven world, statisticians play a crucial role in extracting meaningful insights from complex datasets and building predictive models. This course will provide you with a comprehensive understanding of R programming language, statistical analysis techniques, and machine learning algorithms, enabling you to apply advanced analytical methods to solve real-world problems and enhance decision-making processes.

Course Objectives:

1. Develop proficiency in R programming language for data manipulation, visualization, and statistical analysis.
2. Gain a deep understanding of statistical analysis techniques, including hypothesis testing, regression analysis, and time series analysis, using R.
3. Learn fundamental concepts and algorithms of machine learning, such as supervised and unsupervised learning, classification, and clustering.
4. Acquire practical experience in applying machine learning algorithms in R to build predictive models and perform data-driven decision-making tasks.
5. Explore best practices for model evaluation, validation, and interpretation to ensure the accuracy and reliability of machine learning models.