Full course description
This course, presented in a "Train the Trainer" format, provides a comprehensive overview of artificial intelligence, covering fundamental concepts, technological advancements, and real-world applications. It begins by distinguishing AI from automation and tracing its history, including the evolution of integrated chips. Participants explore emerging AI technologies powered by Big Data, IoT, and 5G, and delve into AI applications across various industries, emphasizing Industry 4.0. The curriculum includes hands-on experience with AI project cycles, data handling, modeling, evaluation, and deployment, with a focus on ethical considerations and societal impacts. Key topics include machine learning (ML) and deep learning (DL) fundamentals, generative adversarial networks (GANs), variational autoencoders (VAEs), and the roles within AI/data science teams. Practical projects using no-code tools for statistical data, natural language processing (NLP), and computer vision are integrated. The course concludes with a forward-looking perspective on AI, discussing future possibilities like quantum computing, hardware acceleration, artificial general intelligence (AGI), and the transformative potential of reinforcement learning.