Data analytics classes for beginners typically cover foundational concepts and skills necessary to analyze data effectively. Students learn how to gather data from different sources and clean it to ensure accuracy and consistency. This involves understanding different data types, dealing with missing values, and handling outliers. Many classes include hands-on projects where students apply what they've learned to real-world datasets. These projects help reinforce concepts and build practical skills utilising tools and softwares such as Excel, Python (with libraries like Pandas, NumPy, and Scikit-learn), and SQL for data manipulation and analysis. By the end of the course, students will be equipped with a solid foundation and the fundamental skills and knowledge needed to apply data analysis techniques in their roles or further build their expertise in the field.
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