advanced-ai-techniques – Aissistance

Advanced AI Techniques

This course explores cutting-edge topics in AI, focusing on advanced techniques, ethical implications, and real-world deployment challenges.

Session 1: Unsupervised and Semi-Supervised Learning (9:00 AM – 10:30 AM)

Clustering algorithms (K-Means, Hierarchical, DBSCAN).

Generative Adversarial Networks (GANs) and Deep Generative Models.

Self-supervised learning and anomaly detection.

Session 2: AI Infrastructure and Deployment (10:45 AM – 12:30 PM)

CPUs vs. GPUs vs. Specialized Chips for AI.

Edge vs. On-Premises vs. Cloud AI deployments.

Open-source AI software and frameworks.

Data management, cost, and scalability for AI.

Lunch Break (12:30 PM – 1:30 PM)

Session 3: Ethical AI and Societal Impact (1:30 PM – 3:00 PM)

Advanced topics in AI ethics: bias, privacy, accountability.

Responsible AI development and governance.

Human trust and acceptance with AI systems.

Session 4: Emerging Trends and Future of AI (3:15 PM – 4:30 PM)

Explainable AI (XAI) and interpretability.

Quantum Computing and its potential impact on AI.

AI-driven advancements and networked autonomy.