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Artificial Intelligence A-Z 2026: Agentic AI, Gen AI, and RL

Artificial Intelligence A-Z 2026 combines Agentic AI, Generative AI, Prompt Engineering, and Deep Reinforcement Learning to build powerful AI systems using AWS and Python. Ideal for those interested in AI development and machine learning.

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Artificial Intelligence A-Z 2026 is a comprehensive course designed to equip learners with the skills to build advanced AI systems. The course covers Agentic AI, Generative AI, Prompt Engineering, and Deep Reinforcement Learning, providing a robust foundation for AI development. Participants will learn to create AI chatbots using AWS PartyRock, a no-code platform, and explore neural networks and activation functions inspired by biological neurons. The course delves into reinforcement learning, illustrating how AI agents learn from their environment through rewards and actions, with practical examples like maze navigation and robotic movement.

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Deep Q-Learning is a key focus, with lectures explaining the integration of neural networks to enhance reinforcement learning. Learners will understand the differences between traditional Q-learning and Deep Q-learning, and how the latter excels in complex environments. The course includes practical tutorials using PyTorch, guiding participants through building neural network architectures for tasks like lunar landing.

The course is suitable for anyone interested in AI, machine learning, or deep learning, offering downloadable Python code templates for easy implementation. With a focus on practical applications, participants will gain valuable insights into AI systems' learning and adaptation processes, preparing them for real-world AI development challenges.

  • CategoryCorporate Training & E-Learning
  • Pricing ModelPaid

  • Agentic AI development

  • Generative AI techniques

  • Prompt Engineering strategies

  • Deep Reinforcement Learning

  • AWS PartyRock platform

  • Neural network fundamentals

  • Deep Q-Learning implementation

  • PyTorch tutorials

  1. Configure: Set up AWS PartyRock for chatbot development

  2. Use: Implement neural networks using PyTorch

  3. Optimise: Enhance AI models with reinforcement learning techniques

  4. Deploy: Launch AI systems using AWS and Python

  • AI Chatbot Development
  • Neural Network Implementation
  • Reinforcement Learning
  • Deep Q-Learning
  • AI System Deployment

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