Brief Introduction
Learn how statistics plays a central role in the data science approach.
Description
This statistics and data analysis course will pave the statistical foundation for our discussion on data science.
You will learn how data scientists exercise statistical thinking in designing data collection, derive insights from visualizing data, obtain supporting evidence for data-based decisions and construct models for predicting future trends from data.
Knowledge
- Data collection, analysis and inference
- Data classification to identify key traits and customers
- Conditional Probability-How to judge the probability of an event, based on certain conditions
- How to use Bayesian modeling and inference for forecasting and studying public opinion
- Basics of Linear Regression
- Data Visualization: How to create use data to create compelling graphics
Python A-Z™: Python For Data Science With Real Exercises!
- 4.7
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Programming In Python For Data Analytics And Data Science. Learn Statistical Analysis, Data Mining And Visualization Learn Python Programming by doing!...
Computational Thinking and Big Data
- 0.0
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Learn the core concepts of computational thinking and how to collect, clean and consolidate large-scale datasets. You will develop skills in data-driven problem design and algorithms for big data....
Applied Statistics with Python
- 0.0
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Analyze data using statistical methods and technology. You’ll learn how to model real-world applications using statistical methods. Upon completing this course, you’ll be able to:...
Foundations of marketing analytics
- 4.6
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Who is this course for? This course is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts....
