DISEASE-RESISTANT WATERMELON VARIETIES ARE THE MOST COST-EFFECTIVE AND ENVIRONMENTALLY SUSTAINABLE SOLUTION. WATERMELON BREEDERS ARE FACED WITH CHALLENGES TO FIND NEW SOURCES OF GUMMY STEM BLIGHT RESISTANCE AS THERE IS NO SINGLE SOURCE OF RESISTANCE IN CULTIVARS. PRESENT PROJECT IS TO IDENTIFY GENETIC LOCI CONFERRING RESISTANCE TO IDENTIFY AND COMBINE QTLS RESISTANT TO GUMMY STEM BLIGHT (GSB). RECENTLY, A PLETHORA OF MACHINE LEARNING APPROACHES SUCH AS DEEP LEARNING (DL) ARE AVAILABLE TO FOR PRECISE PHENOTYPING IN PLANT BREEDING. THESE TOOLS ARE INCREASINGLY BEING USED BY THE PLANT SCIENCE COMMUNITY TO MAKE SENSE OF THE LARGE DATASETS NOW REGULARLY COLLECTED VIA HIGH-THROUGHPUT PHENOTYPING AND GENOTYPING. IN THIS PROPOSAL, WE EXTEND TEACHING DL TOOLS FOR PHENOTYPING AND HOLDING SPECIAL WORKSHOPS FOR STUDENTS TO APPRECIATE LATEST DEVELOPMENTS IN GENOMIC TECHNOLOGIES.