This course offers an intensive, hands-on exploration of machine learning (ML) techniques and their application in the field of cybersecurity. Utilizing a versatile and user-friendly ML platform, students will learn to apply various machine learning algorithms and processes to real-world security challenges. The course covers a range of topics from basic ML concepts to advanced applications in network security, anomaly detection, and ethical considerations. The curriculum is designed to provide a balance between theoretical understanding and practical skills. Students will engage with ML platform’s intuitive interface to implement ML workflows, making the course accessible even to those with limited programming experience. This approach allows students to focus more on understanding the concepts and strategies of machine learning in security, rather than the intricacies of coding. Throughout the course, students will work on hands-on projects and case studies, applying their knowledge to solve practical security problems. The course culminates in a capstone project where students will demonstrate their ability to use machine learning for a comprehensive security solution.