Duration
1 day
Overview
Artificial Intelligence (AI) has been around for quite some time, but recently it has been thrust into the limelight – elevating itself from a far-fetched, science-fiction topic to one that is currently dominating the conversations with customers, partners, and industry leaders across Asia. In the last few years, the convergence of big data, ubiquitous and powerful cloud computing, along with breakthroughs in software algorithms and machine learning have made exciting new scenarios in AI deployment a possibility.
Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy. Machine learning is an important component of the growing field of data science. By statistical methods, algorithms are trained to make classifications or predictions, uncovering key insights within data mining projects. These insights subsequently drive decision making within applications and businesses, ideally impacting key growth metrics. As big data continues to expand and grow, the market demand for data scientists will increase, requiring them to assist in the identification of the most relevant business questions and subsequently the data to answer them.
As AI continues to transform the nature of work, people will need to rethink education, skills, and training to ensure that people are prepared for the jobs of the future and businesses have access to the talent they need to succeed.
Outline
In this webinar, we will address the following topics:
- What is Artificial Intelligence?
- Common Artificial Intelligence Workloads
- Artificial Intelligence in Microsoft Azure
- How Artificial Intelligence Works?
- Where is AI used?
- Introduction to Machine Learning
- How Machine Learning Works?
- Machine Learning Methods
- Real-World Machine Learning Use Cases
- Challenges and Risks with AI
- Principles of Responsible AI
Programme scope, delivery arrangements and suitability are confirmed during enquiry.