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Frequently Asked Questions

Data Science is an interdisciplinary field that combines statistics, machine learning, programming, and domain knowledge to extract insights and knowledge from structured and unstructured data.

A Data Scientist should have strong analytical skills, proficiency in programming languages like Python or R, knowledge of machine learning, data visualization, SQL, and an understanding of statistics and probability.

Data Science is a broader field that includes data analysis, visualization, and predictive modeling. Machine Learning is a subset of Data Science that focuses on algorithms and models that enable computers to learn from data and make predictions.

Data Science is used in various industries, including healthcare (disease prediction), finance (fraud detection), marketing (customer segmentation), e-commerce (recommendation systems), and self-driving cars (computer vision).

Some of the most popular tools include Python (with libraries like Pandas, NumPy, and Scikit-learn), R, SQL, Jupyter Notebooks, Tableau, Power BI, and cloud platforms like AWS and Google Cloud.

You can start by learning Python or R, understanding basic statistics, exploring machine learning concepts, and practicing with real-world datasets. Online platforms like Coursera, Udacity, and Kaggle provide great resources for beginners.