0801 - IBM Skills Academy |Building Trustworthy AI Enterprise Solutions (CE Online)

Language of Delivery English

Delivery Options CE On-Demand

Course Description

This course explores the topics, technology, and skills required to gain practice in the successful application of Artificial Intelligence to address key industry problems.

Learner Outcomes

Throughout the course, you will learn the following objectives:

Understand the evolution and relevance of Artificial Intelligence for the enterprise, and implementation trends across several industries, including: banking, insurance and healthcare.
Deep dive into the heart of AI, exploring several Machine Learning and Deep Learning algorithms including Gradient Boost, Random Trees, Support Vector Machines, and data transformation practices for Visual Recognition and Natural Language Processing AI models.
Explore open-source tools for AutoML and better understand concepts such as Feature Engineering. Model Scoring, Model Decay and Hyperparameter Optimization.
Understand the solutions that will change our reality in the near future by exploring scientific achievements, including the future of AI in healthcare, autonomous marine vehicles, extreme weather, and the science of debate and space exploration.
Learn the fundamentals of using low-code cloud-based AI tools with pre-built ML algorithms to accelerate the end-to-end AI model lifecycle management.
Acquire hands-on experience using AI tools including: IBM Cloud services, IBM Watson Discovery, IBM Watson Assistant, IBM Watson OpenScale, IBM AutoAI, IBM Knowledge Studio and IBM Natural Language Understanding.
Explore an end-to-end Bank Loan case study affected by the COVID-19 pandemic, and their team dynamics as they leverage their digital transformation AI journey to explore new legal service offerings.
Role-play the interdepartmental responsibilities within the Bank, including the role of business sponsors, in collaboration with Data science teams, and the inclusion of an AI ethic leader.
Analyze AI ethical adoption practices within the enterprise including Fairness, Accountability, Privacy, Robustness and Explainability, and the roadmap towards enterprise AI trustworthiness.