Requirements
-
Basic familiarity with and programming and probability distributions, mean, standard deviation, etc would be helpful but not required
Description
AI is an enabler in transforming diverse realms blockchain by exploiting deep learning architectures.
The course aims to expose students with cutting edge algorithms, techniques, and codes related to deep learning routines. This course encompasses multidimensional implementations on the themes listed below;
1. Block Chain and Crypto mining
2. Crypto trading.
3. Forks in Block Chain
4. Impact of Forks on Digital Currency.
5. Green Cryptocurrency
6. Investment Strategies in Crypto- trade.
7. Fungible and Non- Fungible Digital Currencies.
8. Deep Learning Convolutional Networks for AI Healthcare.
9. Role and Management of Big Data Computing in AI Healthcare.
10. How Hadoop and Python is cultivating AI based wellbeing.
11. AI based solutions for Neurological Diseases using Deep Learning.
12. AI for Brain Computer Interfacing and Neuromodulation.
13, AI algorithms for diagnosis, prognosis and treatment plans for Tumors.
14. How to model an AI problem in Healthcare.
15. How to create, preprocess and augment a data set for AI based Healthcare.
16. How to use transfer learning in multiclass classification healthcare problems.
17. Optimizers to be used in Deep learning Healthcare Problems.
18. Leading Convolutional Neural Networks (ALEXNET & INCEPTION) and validation indices.
19. Recurrent Neural Networks extending to Long Short Term Memory.
20. An understanding of Green AI.
21. Implementations of Neural Networks in Keras and Pytorch.
22. Introduction to Quantum Machine Learning.
23. Algorithms related to Quantum Machine Learning in TensorFlow Quantum and Qiskit.
24. Artificial Intelligence in Robotics.
25. Artificial Intelligence in Smart Chatbots.
26. Impact of AI in business analytics.
27. AI in media and creative industries.
28. AI based advertisements for maximum clicks.
29. AI for the detection of Misinformation Detection.
30. Extraction of Fashion Trends using AI.
31. AI for emotion detections during Covid- 19.
Who this course is for:
- Undergraduate final year students, MS, PhD and Postdoctoral students
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