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This course helps you take your knowledge of data and turn it into meaningful insights. Predictive analytics can help you not only understand what your previously collected data show, but what will most likely happen in the future. Learn how to leverage tools to make statistical inferences easy for all people to accomplish and communicate their findings.
This course can be applied to the following certificates:
AI Python Certificate
Data Analysis – Advanced Certificate
Data Analysis Certificate
Benefits and Learning Outcomes
- Understand how predictive analytics can be used to turn data into future information and knowledge
- Use appropriate models of analysis based on the situation or collected data
- Use predictive analytics to solve business or other problems
Course Outline/Topics
Introduction to predictive analytics
- Review of descriptive analytics
- Review of predictive analytics
- Review of prescriptive analytics
- Supervised and unsupervised learning
- Examples of predictive analytics that affect your life
- Variance
- Correlation
- Causation
- Confidence Intervals
Steps to creating a predictive model
- Target and dependent variables
- Predictors and independent variables
- Sample and population
- Null hypothesis
- Collect, gather and manipulate data
Evaluating a predictive model
- Differences in fields
- Accuracy
- Types of error
- Alpha levels
- Comparison of results from models
- Parsimonious models
Supervised learning
- Linear regression
- Logistic regression
- Forecasting
Unsupervised learning
- Clustering
- Association
Prerequisites
It is highly recommended that participants have taken the Data Foundations course or have equivalent experience in data analysis. It is also very helpful to have taken Python or have experience in Python or R prior to this course.