In the first month, students will embark on their journey into the world of Artificial Intelligence (AI) by laying a strong foundation. They will start with an introduction to the history and evolution of AI, gaining insights into the milestones and key figures that have shaped the field. This will set the context for understanding the current landscape and future trends in AI. Students will then delve into the basics of data, learning about data collection methods and preprocessing techniques essential for preparing data for machine learning models. The month will also cover fundamental concepts of machine learning, including the differences between supervised and unsupervised learning, illustrated with real-world examples.

As the month progresses, students will be introduced to neural networks, exploring their architecture and the role of activation functions. They will also learn the basics of Natural Language Processing (NLP), understanding its core components and applications. The hands-on sessions will provide practical experience, starting with setting up a Python environment and building a simple AI model. By the end of the month, students will have a solid understanding of basic AI concepts and practical skills, ready to tackle more advanced topics in the following months.