Course
Feature Engineering with PySpark
- AdvancedSkill Level
- 4.7+
- 394
Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.
Data Manipulation
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
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Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.
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Learn how to identify, analyze, remove and impute missing data in Python.
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Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.
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Develop the skills you need to clean raw data and transform it into accurate insights.
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Learn how to write recursive queries and query hierarchical data structures.
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Learn how to design and implement triggers in SQL Server using real-world examples.
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Learn the fundamentals of using DataLab, an AI-powered data notebook for data analysis and exploration.
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Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.
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Learn to solve increasingly complex problems using simulations to generate and analyze data.
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Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.
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