AI Decisioning Course (3 Modules) Pre-Order

The AI Decisioning course is comprised of three modules that provide coverage of essential AI topics and explore the technologies, techniques and data processing models distinct to enabling autonomous decision-making within AI systems.

Each module has a set of lessons and is further supplemented with exercises and practice questions to help reinforce your understanding of key topics. Completing this course also prepares you for the official certification exam, as explained on the AI Decisioning Specialist Certification page.

Further resources are available to assist you with the completion of this course and preparation for the certification exam. These include downloadable digital course PDFs, printed course materials that can be shipped to your location, as well as coaching and instructor-led training services available by Arcitura and its training partner network. You can purchase coaching time on an hourly basis and instructor-led training workshops are available for individuals and groups.

This course is available via two separate eLearning platforms, each of which has different features and benefits. Upon clicking the Enroll button, you will be able to choose the eLearning option that works best for you.

Contact [email protected] with any questions.

Program: Next-Gen Data Science Academy

Prerequisites: None

Duration: 30 hours

Price: from $19

Corresponding Certification:
AI Decisioning Specialist

Inquire About Instructor-Led Training for Your Team

Workbook Lessons

Video Lessons

Reference Posters

Interactive Exercises

Graded Self-Test

Completion Certificate

Course Modules

MODULE 22 | Fundamental AI Decisioning
Covers essential topics pertaining to AI systems, neural networks and data processing, with an emphasis on autonomous decision-making capability-enablement. Topics include risk assessment, reinforcement learning, decision-result evaluation, ethics and behavior control.

MODULE 23 | Advanced AI Decisioning
Covers advanced topics, such as knowledge representation, rules of inference, probabilistic reasoning and First-Order Logic (FOL) and documents a series of AI practices as applied to autonomous decision-making, including reasoning, data wrangling, reinforcement learning and model evaluation and optimization.

MODULE 24 | AI Decisioning Lab
Provides a series of real-world exercises for utilizing AI practices and techniques to assemble AI-driven, autonomous decisioning solutions for common usage scenarios.