AI Fundamentals

The course "AI Fundamentals" provides an introduction to the field of artificial intelligence (AI), covering its fundamental concepts, applications, and techniques. The course starts with an overview of AI, explaining what it is, its history, and its impact on society. It then explores the main subfields of AI, including machine learning, natural language processing, computer vision, robotics, and expert systems. The course also covers the core principles of AI, including knowledge representation, reasoning, planning, and decision making. It explains how these principles are applied in different AI applications, such as speech recognition, image classification, autonomous driving, and healthcare. Another key topic covered in the course is machine learning, which is the most widely used technique in AI. The course explains the different types of machine learning, such as supervised, unsupervised, and reinforcement learning, and how they are used to train AI models. It also covers the main algorithms and tools used in machine learning, such as linear regression, logistic regression, decision trees, neural networks, and TensorFlow. In addition, the course discusses the ethical and social implications of AI, including bias, transparency, privacy, and job displacement. It also provides an overview of the current state of AI research and development, and the challenges and opportunities ahead. The course is designed for students and professionals who want to learn the basics of AI and its applications. It does not require any prior knowledge of programming or computer science, although basic math and statistics knowledge is helpful. The course is taught by experienced instructors who have expertise in AI and related fields, and who use real-world examples and case studies to illustrate the concepts and techniques covered in the course. The course is delivered online, with interactive lectures, quizzes, assignments, and projects that help students reinforce their learning and apply it in practice. By the end of the course, students will have a solid understanding of the fundamentals of AI, and will be able to apply this knowledge in various domains and contexts. They will also be prepared to further their learning in more advanced AI courses and programs, or to explore career opportunities in the field of AI. Author: Microsoft Azure (Udacity)