Artificial intelligence has become a powerful driving force in a wide range of industries, helping people and businesses create exciting, innovative products and services, enable more informed business decisions, and achieve key performance goals.
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Also known as deep neural learning ordeep neural network
The Artificial Intelligence course is designed to help learners decode the mystery of artificial intelligence and its business applications. The course provides an overview of AI concepts and workflows, machine learning and deep learning, and performance metrics.
It will help to learn the difference between supervised, unsupervised and reinforcement learning, be exposed to use cases, and see how clustering and classification algorithms help identify AI business applications
Artificial Intelligence course will give you a look at the booming field of AI and show you how AI can help drive business value. The course covers basic concepts, terminologies, scope and stages of artificial intelligence and their effect on real-world business processes. By the end of the course, you will be able to clearly define various supervised and unsupervised AI algorithms, apply machine learning workflow to solve business problems and measure ROI based on performance metrics.
Upon completion of this course, you will understand:
- The meaning, purpose, scope, stages, applications and effects of AI
- Fundamental concepts of machine learning and deep learning
- The difference between supervised, semi-supervised and unsupervised learning
- Machine Learning workflow and how to implement the steps effectively
- The role of performance metrics and how to identify their key methods
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