How to learn data science?
Learn the fundamentals of statistics and Python/R before moving on to data science. Use Matplotlib/Seaborn for data visualisation and Pandas for data processing practice. Study model evaluation, machine learning techniques, and big data technologies such as Hadoop and Spark. For more difficult jobs, dive into deep learning with TensorFlow/PyTorch. Complete tasks, take part in contests, and keep up with online groups and resources to promote lifelong learning.
Priyanka Yadav
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khushnuma commented
To learn data science, start by mastering foundational skills in mathematics (especially statistics and linear algebra) and programming (Python or R). Next, learn key data manipulation libraries (e.g., Pandas, NumPy) and data visualization tools (e.g., Matplotlib, Seaborn). Study machine learning algorithms and concepts using libraries like Scikit-learn or TensorFlow. Work on real-world projects and datasets, exploring platforms like Kaggle. Understand databases and SQL for data querying. Enhance your knowledge with online courses (like the Best Data Science Course in Faridabad, Ghaziabad, Delhi, Noida, and other cities in India). Finally, practice consistently, collaborate with peers, and stay updated with the latest trends in the field.
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