This course introduces two highly sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. Deep Learning, a part of Machine Learning (ML), is widely used in various AI applications. The course begins by covering the theory behind Neural Networks, the foundation of Deep Learning, and explores different modern architectures. Following this, the focus turns to Reinforcement Learning, which has recently gained significant attention, although it currently has limited practical applications.
However, it is considered a promising area of AI research for the future. Upon completing this course, in conjunction with the previous courses in the IBM Specialization, learners will have gained considerable practice and a solid understanding of the main types of Machine Learning (ML): Supervised Learning, Deep Learning, Reinforcement Learning, and more.
🆓 Free to Audit
🕒 Approx. 31 Hours
📈 Intermediate Level
🧾 Paid Certificate Available Upon Completion
🎓 Offered by IBM via Coursera
