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Delve into the world of Artificial Intelligence (AI) with our comprehensive overview. Crafted for managers, CTOs, and innovators, this course offers an in-depth look into AI's history, its methodologies, real-world applications, and future prospects. Enrich your understanding of AI's transformative potential, its reasoning mechanisms, and its interactive capabilities.
Dive deeper into the rapidly-evolving realm of Artificial Intelligence. Through this intensive workshop, participants will:
• Revisit AI's Roots: Understand the historical context and evolution of Artificial Intelligence.
• Decipher Intelligent Agents: Gain insights into problem-solving agents and adversarial search strategies.
• Uncover Knowledge & Reasoning: Explore the realm of logical agents, first-order logic, and planning in dynamic environments.
• Tackle Uncertainty: Learn about probabilistic reasoning, quantifying uncertainty, and making both simple and complex decisions in ambiguous scenarios.
• Embark on Learning Journeys: Discover the different methodologies, from learning from examples to reinforcement learning.
• Engage with Communication & Perception: Dive into Natural Language Processing, perception technologies, and the fascinating world of robotics.
• Reflect on AI's Journey: Contemplate the philosophical foundations and envisage AI's present and looming future.
• Broad knowledge of computing, biology, mathematics, and physics.
• An interest in technology trends and innovation.
*We customize the course outline and content to your specific needs and relevant use cases.
1. Artificial Intelligence History: Tracing AI's evolution.
2. Intelligent Agents: The building blocks of AI systems.
3. Problem Solving Techniques:
• Searching strategies
• Beyond classical and adversarial search
• Addressing constraint satisfaction problems
4. Knowledge and Reasoning:
• Introduction to logical agents
• Delving into first-order logic & inference
• Classical planning and real-world applications
5. Handling Uncertainty:
• Quantifying and reasoning with uncertainty
• Time-bound probabilistic reasoning
• Decision-making in uncertain scenarios
6. Learning Paradigms:
• Learning from examples & incorporating knowledge
• Probabilistic model learning
• The dynamics of reinforcement learning
7. Communicating, Perceiving, and Acting:
• Introduction to Natural Language Processing
• Communication with natural language
• Perception technologies and robotics
8. Concluding Remarks:
• Philosophical underpinnings of AI
• Contemplating AI’s current state and future trajectory
Hands-on learning with expert instructors at your location for organizations.
Master new skills guided by experienced instructors from anywhere.
