#9 What topics comes under data science?

Data science is a multidisciplinary field that combines various techniques, algorithms, and theories from statistics, mathematics, computer science, and domain-specific knowledge to extract insights and knowledge from structured and unstructured data. Some common topics within data science include: Statistics: Understanding probability, hypothesis testing, regression analysis, and other statistical methods is fundamental to analyzing data. Machine Learning: Techniques like supervised learning (e.g., regression, classification), unsupervised learning (e.g., clustering, dimensionality reduction), and reinforcement learning are used to build predictive models and uncover patterns in data. Data Mining: Extracting useful information and patterns from large datasets using methods such as clustering, association rule mining, and anomaly detection. Data Cleaning and Preprocessing: Preparing data for analysis by handling missing values, outlier detection, normalization, and transformation. Data Visualization: Communicating insights effectively through the use of charts, graphs, and interactive visualizations. Big Data Technologies: Understanding distributed computing frameworks like Hadoop and Spark for handling large-scale datasets. Database Management: Knowledge of SQL and NoSQL databases for storing and querying data efficiently. Natural Language Processing (NLP): Processing and analyzing human language data, including tasks like sentiment analysis, text classification, and language translation. Deep Learning: Neural network techniques for solving complex problems such as image recognition, speech recognition, and natural language understanding. Domain Knowledge: Understanding the specific domain or industry you are working in to contextualize the data and derive meaningful insights. Visit - https://www.sevenmentor.com/data-science-classes-in-nagpur