Data Science Exploratory Data Analysis 120 unique high-quality test questions with detailed explanations!
Sub Category
- IT Certifications
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Objectives
- Master core EDA concepts including univariate, bivariate, and multivariate analysis techniques.
- Identify missing values, outliers, skewness, and data quality issues using statistical and visualization methods.
- Interpret correlations, feature relationships, and patterns to support data-driven decision making.
- Apply EDA techniques to real-world datasets before building machine learning models.
Pre Requisites
- Basic understanding of statistics concepts such as mean, median, variance, and probability.
- Familiarity with Python fundamentals and basic libraries like Pandas and NumPy.
- Basic knowledge of data visualization tools such as Matplotlib or Seaborn.
- A computer with Python installed (Anaconda/Jupyter Notebook recommended) and willingness to practice with datasets.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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