Skin cancer is a precarious disease caused by unrepaired DNA in skin cells, causing genetic mutations or abnormalities. Skin cancer spreads vigorously that makes it even more challenging to treat during its infancy. Its early detection is crucial for successful intervention. Recent spurt in its incidences, mortality rate, and high costs of medical treatments, several approaches for spotting the disease have been developed by researchers. A distinction between benign and malignant skin cancers can be done on lesion parameters including color, symmetry, form, and size. This detailed study provides a systematic approach and comprehensive examination of Deep Learning Techniques (DLT) for timely identification of skin cancer. Study and analysis focused on research papers pertaining to the subject of skin cancer screening that have appeared in reputable academic publications. Research findings are commonly communicated through various visualization aids, which serve to enhance comprehension and facilitate a deeper understanding of results.