This section of TIMG 5103 (Advanced Topics in TIM) is an in-depth exploration of deep learning and innovation management. It is pre-approved as an analytics elective for the MABA pathway, and is available as a TIMG elective for TIM students on other pathways.
Deep learning is one of the most impactful technologies of our time. This course starts with the history of neural networks and presents the deep neural architectures used today. Topics in the course include convolutional neural networks, autoencoders, generative adversarial networks, recurrent neural networks, deep reinforcement learning, natural language processing, transformers, and neuroevolution. The objective of the course is to teach students the fundamentals, applications, and business impact of deep learning, with an emphasis on solutions to technology innovation management and technology entrepreneurship problems.
TIMG 5103 [0.5 credit]: Advanced Topics in Technology Innovation Management: In-depth exploration of an advanced topic in the field of technology innovation management. A different topic is covered each semester and more than one section, with different topics, may be offered in the same semester.
- Manager: Steven Muegge
- Instructor: Navneet Bhalla