- About the Forecasting and Predictive Analytics Certificate
- Learning Outcomes
- Key Topics covered
- OTHER DETAILS
Earners of the Forecasting and Predictive Analytics Certificate can apply regression, classification, clustering, optimization, and simulation techniques, all used for predictive analytics. Badge earners can forecast and predict future values for increasingly sophisticated data sets and business problems using time-based data. These candidates calculate scenarios based on distance and space, and determine the fit and usefulness for prediction of models.
This certificate is Part 4 of the Data Analyst Certificates Bundle – a comprehensive five-part program that provides training and practical guidance on the topic of data analytics.
The Forecasting and Predictive Analytics Certificate will teach you fundamental techniques used for predictive analytics: regression, classification, clustering, optimization, and simulation. Beginning with basic models for revealing and establishing relationships, you will learn to apply increasingly sophisticated modeling techniques for practical data analysis, as well as commonly encountered problems so you can determine the fit and usefulness for prediction of your models, and apply them to typical business problems.
As you develop your understanding of applied predictive analytics, you'll learn how to perform basic forecasting using time-based data to predict future values from a model. You will also learn how to model and calculate scenarios based on distance and space. You will get practice with classification, including naive Bayesian classification; create basic decision trees; and use various techniques for clustering and linear optimization to solve common business problems; as well as learn techniques for assessing the effectiveness of your solutions.
Note: It is recommended that you complete the Data Analytics Modeling Certificate, or ensure you have equivalent knowledge and skills, before starting this certificate course.
Learning Labs: This is an interactive learning program that includes bonus simulated learning labs with step-by-step guidance. This is an interactive learning program that includes bonus hands-on learning labs that will expose you to the tools needed to implement an analytics practice in a practical way and equip you to deploy those tools as needed within your organization. You will practice using various technologies for preparing, analyzing and managing datasets in the real world. *Time spent on learning labs does not award CPE and completing learning labs is not a requirement for earning the certificate.
Accounting and finance professionals, especially those interested in learning and applying data analysis techniques to help their organizations make informed, data-driven business decisions.Other information
|Format:||Course - Online|
|Access:||This is a digital product. You will have access to the content for a year after purchase date.|
You have twelve (12) months from the date of purchase to complete the entire program.
- The certificate course subscription validity period is for 12 Months respectively.
- Students will receive an activation directly from AICPA within 3 working days
All students will get a digital badge upon completion. A digital badge helps you gain recognition for earning your certificate by allowing you to easily display and share your achievement. Prospective clients and employers will be able to quickly verify your competencies and skills. The digital badge also provides greater credibility and visually declares your commitment to quality. According to a recent LinkedIn study, profiles with certifications and badges receive six times the number of profile views.
- Identify the different techniques of predictive analytics: regression, classification, clustering, optimization, and simulation.
- Calculate varying types of regressions using R and Excel.
- Apply classification and clustering algorithms.
- Apply business process optimization to problems by identifying goals and constraints.
- Analyze the various probabilities of outcomes by applying Monte Carlo simulation.
- Calculate performance of predictive analytic algorithms.
- Predictive analytics techniques
- Forecasting with data models
- Finding relationships in data
- Bivariate and multivariate linear regression
- KNN classification
- Decision trees
- Training models