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Here are some of the top data science tools every data scientist should know:

Python: One of the most popular programming languages for data science due to its simplicity and rich ecosystem of libraries like Pandas, NumPy, Matplotlib, Scikit-learn, and TensorFlow.
R: Another essential programming language for data analysis and statistical computing, offering various packages like ggplot2, dplyr, and caret for data visualization and modeling.
Jupyter Notebooks: An open-source tool that allows interactive coding and visualization, making it ideal for data cleaning, modeling, and presenting results.
Apache Hadoop: A framework that allows for distributed storage and processing of large datasets, making it a go-to solution for big data applications.
Apache Spark: Known for its speed and scalability, Spark is used for handling large-scale data processing, machine learning, and real-time analytics.
Tableau: A powerful data visualization tool that helps data scientists turn raw data into meaningful insights through dashboards and visual analytics.
Power BI: A business analytics tool that offers interactive data visualizations and business intelligence capabilities for creating reports and dashboards.

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