AI & ML
1. How AI is disrupting education
2. What are the forces at play in the software market place?
3. Career Opportunities with AI for students
4. What are the new jobs created by AI?
5. Why is it important to student reskill to AI?
6. Skills needed for AI market?
7. What are other institutions doing to pivot their path?
Reskilling Options for students
AI Adoption pathways
Strategies to implement AI in education
Topics Covered 1. Use machine learning, data mining and statistical techniques on terabytes of clinical data. 2. Design and develop cutting edge clinical NLP and imaging techniques. 3. Deploy models in real-world clinical scenarios. Internship Highlights: 1. Programming languages: Python, Java 2. ML frameworks: Tensorflow, Pytorch. 3. NLP concepts such as information extraction, a bag of words, word embeddings. 4. Computer vision concepts such as image segmentation using deep learning. 5. Knowledge of RNN, LSTM, and other neural network architectures.