Predictive Modeling: Predictive Analytics & Exploratory Data Analysis
Predictive Analytics
| Intermediate
- 9 videos | 40m 36s
- Includes Assessment
- Earns a Badge
Explore the machine learning predictive analytics, exploratory data analytics, and different types of data sets and variables in this 9-video course. Discover how to implement predictive models and manage missing values and outliers by using Python frameworks. Key concepts covered in this course include predictive analytics, a branch of advanced analytics, and its process flow, and learning how analytical base tables can be used to build and score analytical models. Next, you will discover business problems that can be resolved by using predictive modeling; how to build predictive models with the Python framework; and learn the essential features of exploratory data analysis. Then learn about data sets, collections of data corresponding to the content of a single database or a single statistical data matrix, and then learn the variables of the different types of data sets including univariate, bivariate, and multivariate data and analytical approaches that can be implemented with them. Finally, you will learn about methods that can be used to manage missing values and outliers in data sets.
WHAT YOU WILL LEARN
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Define the predictive analytics and describe its process flow
Describe analytical base table and how it can be used to build and score analytical models
Identify the business problems that can be resolved using predictive modeling
Build predictive models using the python framework -
List essential features of exploratory data analysis
Describe univariate, bivariate, and multivariate data and analytical approaches that can be implemented with them
Specify methods that can be used to manage missing values and outliers in datasets
List applications of predictive analytics, describe analytical base tables, list predictive models, and specify variable selection methods
IN THIS COURSE
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1m 30s
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8m 23sIn this video, you will learn how to define predictive analytics and describe its process flow. FREE ACCESS
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3. Analytical Base Table4m 45sAfter completing this video, you will be able to describe an analytical base table and how it can be used to build and score analytical models. FREE ACCESS
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4. Business Problems and Predictive Modeling7m 15sTo identify the business problems that can be resolved using predictive modeling, consult resources that explain the process. FREE ACCESS
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5. Predictive Modeling with Python3m 27sIn this video, you will learn how to build predictive models using the Python framework. FREE ACCESS
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6. Exploratory Data Analysis3m 42sAfter completing this video, you will be able to list essential features of exploratory data analysis. FREE ACCESS
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7. Dataset and Variables Types5m 56sUpon completion of this video, you will be able to describe univariate, bivariate, and multivariate data and the analytical approaches that can be implemented with them. FREE ACCESS
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8. Missing Values and Outlier Management3m 47sAfter completing this video, you will be able to specify methods for managing missing values and outliers in datasets. FREE ACCESS
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9. Exercise: Predictive Modeling with Python1m 52sUpon completion of this video, you will be able to list applications of predictive analytics, describe analytical base tables, list predictive models, and specify variable selection methods. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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