STAT 316 - Big data statistics in genomic and genetic research Learning Course

[STAT 316 - Big data statistics in genomic and genetic research Learning Course] STAT 316 - Big Data Statistics in Genomic and Genetic Research STAT 316 explores the application of big data analytics and statistical methods in genomic and genetic research. The course covers topics such as genome-wide association studies (GWAS), next-generation sequencing data analysis, population genetics, and personalized medicine. Emphasis is placed on understanding the statistical challenges posed by large-scale genomic datasets, including data preprocessing, quality control, variant calling, and statistical inference of genetic associations. Through hands-on exercises and case studies, students learn how to apply advanced statistical techniques, machine learning algorithms, and bioinformatics tools to analyze genomic data, identify genetic variants associated with diseases or traits, and interpret biological insights from genomic studies. The course prepares students for careers in genomic research, precision medicine, and biotechnology by providing practical skills in big data analytics, computational biology, and statistical genetics.This Learning Course is a platform that helps students to study and learn. The platform provides all the required material for the students to study. The material includes Study guide, Exam Questions & Answers, Study Notes and other resources that are useful for the students. It also gives information about the upcoming exams so that students can prepare themselves accordingly.