Data Analysis
Data analysis involves the process of inspecting, cleaning, transforming, and modeling data to uncover insights, patterns, and trends. In the context of Python and R, data analysis encompasses utilizing libraries like Pandas, NumPy, and tidyverse to manipulate and analyze data efficiently. This includes tasks such as exploratory data analysis (EDA), statistical analysis, regression, classification, clustering, and hypothesis testing. Data analysis serves as a crucial step in decision-making and problem-solving across various domains.
Prerequisite for Data Analysis
- Math for Data Analysis
- SQL for Data Analysis
Data Analysis – Python
Data Analysis – R
- R for Data Analysis
- Data Analysis with R
- Data Analysis R Projects
What is AI ML DS and How To Get Started?
In this AI-ML-DS tutorial, you’ll find a wealth of resources designed to demystify these complex fields and empower you to develop practical skills and insights. Whether you’re just starting or looking to deepen your understanding, our tutorials cover everything from the basics of AI and ML algorithms to advanced data science techniques.
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