Petabytes of data are being generated by society and businesses; thanks to artificial intelligence (AI), we can use this data to enhance wellbeing, boost revenue, and cut expenses. With the help of contemporary technology, we may use both internal and external, organized and unstructured data, and apply Artificial Intelligence to open up new possibilities for making predictions, improving decision-making, enhancing business performance, and enhancing human capabilities.
This course equips participants with the AI literacy they need to be the business AI leaders in their organizations. Participants will gain an understanding of AI concepts and use cases, be able to communicate intelligently with data specialists, develop an AI strategy, build an organization that is AI ready, set up and manage AI projects, and evaluate whether to make or buy tooling.
Describe the idea of AI and all of its uses.
Utilize various AI applications throughout the corporate value chain.
Showcase the AI-related technologies and algorithms.
Using an AI project's efforts, implement best practices
Examine the skills and abilities that are both available and required.
Discuss pertinent issues in length with business and data experts.
Create and implement an AI strategy, and build an organization that is AI ready.
This course is intended for senior, medium, and high potential management who realize that disruption, innovation, and continuous improvement are all essential components of doing business and who want to prepare for and benefit from Artificial Intelligence.
In other words, rather than understanding the technical approaches of what occurs inside its body, this course is for managers who want to recognize what AI can accomplish for them and to drive Digital Transformation.
AI in historical setting and combinatorial technologies
Introduction to AI, concepts, narrow and general AI
Different types of AI
AI - sense, reason, act
The thinking in AI: Machine learning
Looking back, now, forward
4 types of data analytics
Analytics value chain
Structured and unstructured data
The 5 V’s of data
Data governance
Supervised learning
Unsupervised learning
Reinforcement learning
Just enough to understand the data architecture
Big data reference architecture
3 categories of data usage
Successful use cases by Porter’s value chain
Primary activities
Supporting activities
Successful use cases by technology
NLP
Image recognition
Machine learning
AI Funnel process
Several idea generation approaches
Prioritize projects
AI project canvas
Use the AI strategy cycle
Dimensions of the AI framework
Practical approach to assess the AI maturity of the organization
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