Synopsis
The term artificial intelligence (AI) refers to a set of computer science techniques that enable systems to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making and language translation. Machine learning and deep learning are branches of AI which, based on algorithms and powerful data analysis, enable computers to learn and adapt independently.
Artificial intelligence (AI) is no longer the future. For businesses, it is the here and now, and executive suites and boardrooms around the world see it as such. They might be expected to be wary, given that much is unknown, even among scientists, about how AI capabilities might develop in the coming years. Or that policymakers and regulators have barely begun to study its potential implications for markets and workforces. Many business leaders certainly expect AI to be disruptive. More than 40% of those surveyed for the study anticipate that AI will start displacing humans from some jobs in their industry within the next five years.
Slightly more think their own role will be changed by AI in the same time frame. But they see this more as augmentation than marginalization. An overwhelming majority believe AI will make their job easier and help improve their own performance. They clearly believe it will do the same for the businesses they manage. Based on a global survey of 203 senior executives, companies in health and life sciences, in retail, in manufacturing and in financial services are actively testing the waters. Among this group, AI technologies and applications are in the exploratory phase at around one-third of companies, but another third have moved on to experimentation, and one-tenth have begun to utilize AI in limited areas. A small handful (2.5%) have even deployed it widely.
Assuming minimal prior knowledge, this course provides complete coverage of the key aspects and topics in Artificial
Intelligence today, including how all the technologies fit together into a complete solution, the applications of AI such as image and speech recognition, search, clustering, optimization, prediction, and understanding data, and how executives can start on their AI journeys.
Learning Objectives
Acquire an understanding of the key trends in AI and how these are influencing the future of business
Identify which areas of your business are ripe for automation and digital transformation
Gain confidence in the management of AI projects
Course Outline :: Artificial Intelligence for Executives::
Identify the pitfalls and ethics concerns associated with AI
Prerequisite
Exposure to Business Intelligence
Exposure to Data Storage Solutions/Databases
Target Audience
C-level executives
Senior Level Managers
Course Outline
Introduction to Artificial Intelligence (60 min)
Origins of Artificial Intelligence and a brief history of the AI revolution
The AI landscape
AI and Digital Transformation
Artificial Narrow Intelligence vs. Artificial General Intelligence
Predictive vs. Prescriptive AI
AI in Recent Times (30 min)
The role of Big Data
Cloud Computing and AI
Mobile Computing and AI
Break (15 min)
Machine Learning and Deep Learning (120 min)
Image Recognition
Speech Recognition
Search
Clustering
NLP
Optimization
Prediction
Understanding Data – Pattern Recognition
AI Application in Business (90 min)
Applying the AI framework
Course Outline :: Artificial Intelligence for Executives::
Employee on-boarding
Invoice processing
Payments
Logistics and SCM
Customer Service and Ticketing
Robotics
IoT
Break (15 min)
Model Creation and Validation (90 min)
Prediction: linear regression, nonparametric regression
Forecasting: ARIMA and RNN’s.
Classification: logistic regression, decision trees, SVM’s.
Clustering: k-means, hierarchical clustering.
Supervised vs. unsupervised vs. semi-supervised learning.
Dimension reduction: principal components
Languages and environments (e.g. R, Python) and standards (PMML).
Data Visualization (30 min)
Practical and effective visualization: beyond bar charts.
Finding the unexpected: the role of visualization in exploratory analysis
Communicating findings: the role of visualization in communicating Data Science outputs.
Standard tools: R, Tableau, D3
AI In Action (60 min)
How AI is enhancing customer engagement
How AI is optimizing business processes – BPA
How AI is generating insights – pattern recognition
Break (15 min)
Starting an AI Journey (90 min)
Aligning AI with Business Strategy
Understanding your AI ambitions
Assessing your AI maturity
Creating your AI heat map
Developing the AI Business Case
Understanding Change Management
Developing your AI Road Map
Course Outline :: Artificial Intelligence for Executives::
Creating your AI Strategy
AI Prototyping (60 min)
Build vs Buy vs Platform
Creating your first AI product
Understanding Data Training and Tuning
The challenge of poor data and unintended bias
Becoming over-dependent on AI
Hands-on Exercise – Discussion on Building an AI-Driven Enterprise (60 min)
Identify which areas of your business are suitable for AI
The role of high-level management in enabling AI decisions
Creating a data-driven business and the infrastructure to deliver it
The ethics of AI
Case Studies (60 min)
Case studies in Manufacturing, Finance and Healthcare
Future-proofing your Business
The Next opportunities for AI
Q&A (30 min)
Programme scope, delivery arrangements and suitability are confirmed during enquiry.