• Evolution of Generative Models • Introduction to generative models (GANs, VAEs, etc.). • Development and evolution of generative models. • Transfer learning and fine-tuning for generative models. • Progressive GANs and training stability. • Prompt Engineering and Generative AI. • Reinforcement learning in generative models. • Using generative models for creative design processes. • Generative AI for interactive experiences. • Human-AI collaboration in creative processes. • Making generative models more interpretable. • Understanding and explaining decisions made by generative models. • Cross-disciplinary Collaboration between generative AI and other fields (e.g., art, science, finance). • Time Series Analysis with Generative Models. • Bayesian Generative Models. • Quantum Generative Models. • Generative AI and Internet of Things. • Generative AI and Big Data Analytics.
• Image synthesis and manipulation. • Generative AI in content creation. • Text generation and natural language processing. • Video generation and deepfake technology. • Music and audio synthesis. • Generative AI in healthcare. • Robotics and automation. • Applications of generative design in architecture and engineering. • Solving optimization problems using generative models. • Decision support systems with generative AI. • Augmented Reality and generative AI. • Generative AI in Education. • Graph Neural Networks (GNNs) and Applications. • Generative AI for Personalisation and Recommendation Systems. • Generative AI for Sustainable Development.
• Ethical issues in generative models. • Addressing biases in generated content. • Ethical implications of deepfakes. • Detecting and preventing malicious use of generative models. • Security challenges in the era of deepfakes. • Emerging trends in generative AI research. • Potential applications on the horizon. • Differential Privacy in Machine Learning
• Foundations of Data Science • Learning Techniques and Applications • Big Data Analytics and Processing • Predictive Modeling and Forecasting • Natural Language Processing and Text Analytics • Computer Vision and Image Analytics • Explainable AI and Model Interpretability • Ethics and Responsible AI in Predictive Analytics • Deep Learning Advances • Data Visualization and Storytelling • Human-AI Collaboration and Augmented Analytics • Real-Time Analytics and Stream Processing • Data Engineering and Pipeline Automation • Reinforcement Learning and Optimization • Data Ethics, Privacy, and Security • Personalization and Recommendation Systems • Geospatial Data Science and GIS Analytics • Predictive Analytics in Healthcare • Data Science for Smart Cities and IoT • Emerging Trends in Predictive Analytics
• Cryptography in Mobile and Wireless Communications • Watermarking and Steganography • Multimedia Security • Public key and conventional algorithms and their implementations • Cryptanalytic attacks and Cryptographic protocols • Pseudo-random sequences • Digital signature and key management • Privacy and security in healthcare • IOT security • Cryptography in Financial Technologies • Quantum Cryptography • Differential Privacy
Early Bird Registration Fees Category Fees Faculty/Academician Participants ₹8000.00 Research Scholars/Students ₹7000.00 Industry Participants ₹10000.00 Foreign Participants $300.00
