Deep Learning via GANs: Healthcare, Conv AI Applications

Generative Artificial Intelligence: 25+ Coding Solutions via AlexNet, ResNet & Inception Models & their implentations

AI is an enabler in transforming diverse realms by exploiting deep learning architectures.

What you’ll learn

  • Learn to model Artificial Intelligence using GANs: AlexNet, Inception to ResNet architectures for Computer Vision and Bioinformatics.
  • GAN Architectures- Introduction and Different GAN Methods.
  • Data Augmentations using GANs.
  • TensorFlow Quantum for training and testing of Hybrid Quantum Neural Networks for Computer Vision in Healthcare(Python).
  • Applied Artificial Intelligence: Concept to diverse practical implications.
  • Applied AI nurturing healthcare: Code Examples using Python programming.
  • 20+ Coding Exercises and Solutions in Open CV for Computer Vision.
  • Implementations of Transfer Learning and GANs in AlexNet, Inception & ResNet for various real life AI centric applications.
  • How to build and implement leading AI architectures in Keras and TensorFlow Quantum with emphasis on medical computer vision.

Course Content

  • How Artificial Intelligence is using Big Data to model Deep Neural Networks –> 2 lectures • 15min.
  • How to Model, Train and validate a deep learning Classifier in Python –> 1 lecture • 8min.
  • Introduction to GANs –> 1 lecture • 10min.
  • Data Augmentation using GANs –> 1 lecture • 6min.
  • GAN Architectures –> 1 lecture • 1min.
  • Transfer Learning in GANs –> 1 lecture • 7min.
  • Training of GAN Architectures –> 1 lecture • 1min.
  • Optimizers in AI, Back-propagation and hyperparameters in AI –> 1 lecture • 7min.
  • GANGough for Data Augmentation –> 1 lecture • 7min.
  • LSTMs and Tiny AI –> 2 lectures • 13min.
  • Modeling and Implementation of Medical Imaging Problems in Python using AI –> 2 lectures • 13min.
  • Implementation of GANs for Neurodegenerative Diseases using AI –> 1 lecture • 8min.
  • BCI- Brain Computer Interfacing using AI –> 1 lecture • 10min.
  • Implementation of GANs in Deep Learning Networks for Cancer Detection –> 1 lecture • 8min.
  • Green Artificial Intelligence –> 1 lecture • 5min.
  • DarkNet Model using Vetex AI –> 1 lecture • 8min.
  • Quantum Machine Learning using Pytorch, Qiskit and TensorFLow Quantum –> 1 lecture • 12min.
  • Artificial Intelligence: A Case Example of Cryptocurrency –> 1 lecture • 7min.
  • Deep learning for implementing Forks in Block chain –> 2 lectures • 11min.
  • AI for Green Cryptocurrencies –> 1 lecture • 7min.
  • Artificial Intelligence in Smart Chatbots –> 1 lecture • 7min.
  • Misinformation Detection using Deep Learning –> 1 lecture • 8min.
  • Smart Social Media Marketing and Business Analytics using AI –> 1 lecture • 11min.
  • 20+ Coding Exercises & Solutions in Open CV (Computer Vision) –> 1 lecture • 1min.

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AI is an enabler in transforming diverse realms by exploiting deep learning architectures.


The course aims to expose students to cutting-edge algorithms, techniques, and codes related to AI and particularly the Generative Adversarial Networks used for data creation in deep learning routines. This course encompasses multidimensional implementations of the themes listed below;


1. Deep Learning: A subset of Hybrid Artificial Intelligence

2. Big Data is Fueling Applied AI.

3. How to model a problem in AI using datasets in Python (Keras & TensorFlow Libraries).

4. Data Augmentation using GANs in Hybrid Deep Learning Networks.

5. How to use Transfer Learning in Hybrid GAN Networks.

6. How to use transfer learning in multiclass classification healthcare problems.

6. Backward Propagation and Optimization of hyper-parameters in AI GANs.

7. Leading Convolutional Neural Networks (ALEXNET & INCEPTION) using GANs and validation indices.

8. Recurrent Neural Networks extending to Long Short Term Memory.

9. An understanding of Green AI.

10. Implementations of Neural Networks in Keras and Pytorch and introduction to Quantum Machine Learning.

11. Algorithms related to Quantum Machine Learning in TensorFlow Quantum and Qiskit.

12. GANs for Neurological Diseases using Deep Learning.

13. GANs for Brain-Computer Interfacing and Neuromodulation.

14, GAN based AI algorithms for diagnosis, prognosis, and treatment plans for Tumors.

15. How to model an AI problem using GAN in Healthcare.

16. AI in BlockChain and Crypto mining

17 AI in Crypto trading.

18. Forks in Block Chain via AI.

19. Investment Strategies in Crypto- trade using AI (Fungible and Non- Fungible Digital Currencies).

24. Artificial Intelligence in Robotics- A case example with complete code.

25. Artificial Intelligence in Smart Chatbots- A case example with complete code.

26. Impact of AI in business analytics- A case example with complete code.

27. AI in media and creative industries- A case example with complete code.

28. AI based advertisements for maximum clicks- A case example with complete code.

29. AI for the detection of Misinformation Detection.

30. Extraction of Fashion Trends using AI.

31. AI for emotion detections during Covid- 19.

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