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In this course, you will :
- Cover the data science workflow and how data science is used to solve real-world problems
- Understand the data science workflow, we'll look at the first step: data collection and storage.
- Learn about the various data sources available, what that data looks like, how to store it once collected, and how a data pipeline can automate the process.
- how to diagnose data problems, deal with missing values, and outliers
- You will then learn about visualisation, which is another important tool for both exploring your data and communicating your findings.
- Talk about experimentation and prediction! Beginning with experiments, we'll go over A/B testing before moving on to time series forecasting, where we'll learn how to predict future events.
Syllabus :
- Introduction to Data Science
- Data Collection and Storage
- Preparation, Exploration, and Visualization
- Experimentation and Prediction
