COURSE OVERVIEW

This course is designed to provide participants with a detailed and up-to-date overview of Introduction to Artificial Intelligence - Concepts, History & Applications. It covers the scope of AI and its importance in modern industries; the AI technologies and branches covering machine learning (ML), natural language processing (NLP), computer vision for image recognition, processing, robotics and autonomous systems; the symbolic AI and rule-based systems and statistical AI and probabilistic models, evolutionary computing, genetic algorithms and hybrid AI approaches; and the AI in personal assistants, powered recommendation systems, healthcare and diagnostics and driven customer service chatbots.

 

Further, the course will also discuss the types and applications of machine learning (ML) and the differences between AI, ML and deep learning; the supervised and unsupervised learning, deep learning, neural networks and natural language processing (NLP); the AI in computer vision and image processing, healthcare, medicine, finance and banking; the AI in manufacturing and automation, retail and e-commerce as well as autonomous vehicles and smart cities; the examples of bias in AI models and addressing bias in AI systems; and the ethical AI development and best practices.

During this interactive course, participants will learn the data privacy, AI applications and AI-driven surveillance and its implications; the regulations and policies governing AI privacy; the automation of repetitive tasks and impact on employment; the rise of AI-driven job roles and career opportunities; the deepfake technology, AI in misinformation, fake news generation and how to mitigate AI-generated misinformation; the AI governance and responsible AI development and the future trends in AI and emerging technologies; and the AI and human augmentation, space exploration and scientific research and creative industries covering art, music and writing.