- Data: The foundation of data science. It involves collecting, cleaning, and organizing data to make it usable for analysis.
- Big Data: Handling massive datasets that traditional data processing tools can’t manage. Big Data technologies like Hadoop and Spark help in storing and processing these large volumes of data.
- Machine Learning: The heart of data science. Machine learning algorithms enable computers to learn from data and make predictions or decisions without being explicitly programmed.
- Statistics and Probability: Essential for analyzing data and making inferences. These mathematical tools help in understanding data patterns, relationships, and trends.
- Programming Languages: Tools like Python, R, and SQL are crucial for implementing data science projects. They help in data manipulation, analysis, and visualization.
