Displaying 1-11 of 11 results
Basic data descriptors, statistical distributions and application to business decisions
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- Coursera
This course is designed to introduce you to business statistics. The ability to understand and apply business statistics is becoming increasingly important in the industry. A good understanding of business statistics is a requirement to make correct and relevant data interpretations.
Business applications of hypothesis
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- Coursera
Confidence intervals and hypothesis tests are very important tools in the business statistics toolbox. A mastery over these topics will help enhance your business decision-making and allow you to understand and measure the extent of risk or uncertainty in various business processes.
Business statistics and analysis specialisation
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- Coursera
Build data analysis and business modelling skills. Gain the ability to apply statistics and data analysis tools to various business applications.
Data Science A-Z™
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- Udemy
This course will give you a full overview of the data science journey. Upon completion, you will know: how to clean and prepare your data for analysis; how to perform basic visualisation of your data; how to model your data; how to curve-fit your data; and how to present your findings.
Deep Learning A-Z™: Hands-on artificial neural networks
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- Udemy
Learn to create deep learning algorithms in Python from two machine learning and data science experts. Templates included.
Exploratory data analysis
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- Coursera
This course covers the essential exploratory techniques for summarising data. These techniques are typically applied before formal modelling starts and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data.
Introduction to probability and data
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- Coursera
This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualisation.
Linear regression and modelling
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- Coursera
This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. In this course, you will learn the fundamental theory behind linear regression and, through data examples, learn to fit, examine and use regression models to examine relationships between multiple variables, using the free statistical software R and RStudio.
Machine Learning A-Z™: Hands-on Python and R In data science
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- Udemy
Learn to create machine learning algorithms in Python and R from two data science experts. Code templates included.
Predictive modelling and analytics
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- Coursera
This course will introduce you to some of the most widely used predictive modelling techniques and their core principles. By taking this course, you will form a solid foundation for predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on data.
Statistics for data science and business analytics
- Website
- Udemy
Statistics you need in the office: descriptive and inferential statistics, hypothesis testing and regression analysis.
Displaying 1-11 of 11 results