Data science involves extracting insights and knowledge from complex and large datasets using a combination of statistics, programming, and domain expertise. It encompasses data collection, cleaning, exploration, and modeling, often employing machine learning techniques. The goal is to uncover patterns, make predictions, and drive informed decision-making across various fields, from business and healthcare to social sciences. Successful data science requires a blend of analytical skills, domain knowledge, and effective communication to translate findings into actionable solutions.
Machine learning is a branch of artificial intelligence that enables computers to learn patterns from data. It involves creating algorithms that can improve their performance over time by adapting to new information. This approach is used for tasks like image recognition, language translation, and recommendation systems. Machine learning models are trained on data to make predictions or decisions without being explicitly programmed. Common techniques include supervised learning, unsupervised learning, and reinforcement learning.