Developing critical thinking and applying it successfully to data, the life blood of business is a must have skill-set for the Chartered Accountant of Tomorrow. Being well grounded in Data Analytics and being data savvy will help to differentiate Chartered Accountants and Canadian CPAs employed in Finance, Audit, Tax and Executive Leadership roles. CAW Network USA is delighted to announce our partnering with AICPA to offer up their Data Analytics course at 24% off non-AICPA member rates. The AICPA class comprises 5 distinct data analytics modules which can be purchased as a complete course or individually, each giving CPE credits and a certificate of completion.
These are excellent hands on courses that will develop your familiarity and confidence in applying Data Analytics concepts and strategies, from the ground up. To get the member rate use coupon data24 at checkout.
DATA ANALYST BUNDLE
Bundle Price
Includes
- Core Concepts – 8 credits
Our price $300.20 – (AICPA non-member price $395) - Application of Data Analytics Essentials – 14 credits
Our price $759.24 (Non-member price $999) - Data Analytics Modeling – 14 credits
Our price $668.04 (Non-member price $879) - Forecasting and Predictive Analytics – 15 credits
Our price $684 (Non-member price $900) - Data Visualization – 10 credits
Our price $684 (Non-member price $900) - Total CPE- Worth 61 CPE Credits!
- *To get the member rate use coupon data24 at checkout.
Learning Outcomes
- Define the characteristics of an analytical and data-driven mindset.
- Recognize how to establish objectives and desired outcomes of a data analytics project.
- Recognize ways data is applied and interpreted.
- Calculate meaningful statistics, including central tendency, measurement and variability, basic probability, conditional probability, advanced probabilities, discrete distributions, and continuous distributions.
- Identify opportunities, processes, and necessary data for solving analytical problems.
- Align the outcomes of your data analytics practice with your organization’s strategic direction and create value.
- Identify different techniques of predictive analytics: regression, classification, clustering, optimization, and simulation.
- Formulate a data story using visualization tools.