In the Data Science specialization, you will delve into the field of data analysis and learn techniques to extract valuable insights from vast amounts of data. You will study data mining, statistical analysis, machine learning, and data visualization, equipping you with the skills to make data-driven decisions and contribute to the growing field of data science.
Statistical Inference and Modelling
Statistical inference uses sample data to make generalizations about a population through methods like hypothesis testing and confidence intervals, assessing the reliability of conclusions. Statistical modelling creates mathematical models to represent relationships within data. Techniques such as linear regression and logistic regression predict outcomes and identify patterns.
Data Science Principles
Data science principles involve extracting insights from data using techniques like statistical analysis, machine learning, and data visualization. Key steps include data collection, cleaning, exploration, and modeling. These principles enable informed decision-making and problem-solving across various fields, transforming raw data into valuable information that drives innovation and efficiency.
Data Mining
Data mining involves extracting valuable information from large datasets using techniques such as clustering, classification, regression, and association rule learning. It encompasses data preprocessing, pattern discovery, and knowledge extraction to uncover hidden patterns, trends, and correlations. This process aids in decision-making, predictive analysis, and strategic planning across various industries, transforming raw data into actionable insights.