Mind of the Machine: Understanding Cognitive Processes and Decision-Making in AI and ML
- Overview
- Course Content
- Requirements & Materials
COURSE ID: DEF 1102P
Mind of the Machine: Understanding Cognitive Processes and Decision-Making in AI and ML
Course Description
Unveil the cognitive capabilities of AI in this immersive two-day course tailored for individuals with basic AI understanding. Delve into how AI mimics human decision-making and learns from data through hands-on exercises and a project-focused approach. Using Python and Jupyter notebooks, participants will build and enhance neural networks, applying their skills to real-world scenarios like medical imaging, autonomous vehicles, and security applications. Master advanced techniques in data preprocessing, ensemble methods, and reinforcement learning to design sophisticated AI systems.
Cognitive Processes in AI
- Compare human and AI cognitive functions.
- Discuss cognitive psychology's impact on AI.
- Examine neural network structures akin to human brains.
- Review case studies of AI mimicking human cognition.
Learning from Data
- Employ methods for large and complex datasets.
- Apply data augmentation, feature engineering, and reduction.
- Utilize transfer learning and ensemble methods.
- Implement strategies against overfitting and underfitting.
Decision-Making Mechanisms
- Deepen knowledge of decision trees and gradient boosting.
- Understand exploration vs. exploitation balance.
- Analyze AI decisions in healthcare and finance.
- Evaluate and validate AI decision-making through case studies.
Reinforcement Learning and Autonomous Systems
- Learn reinforcement learning basics: reward, policy, and value function.
- Examine applications in gaming and robotics.
- Explore deep reinforcement learning and multi-agent systems.
- Discuss real-world applications in reinforcement learning.
Ethical Considerations and Bias in AI
- Identify bias sources in algorithms and data.
- Employ techniques to detect and mitigate bias.
- Apply ethical frameworks in AI development.
- Study impacts of biased AI decisions through case studies.
Explainability and Interpretability in AI
- Discuss the critical role of explainability in applications.
- Learn techniques for making AI models interpretable.
- Explore current research in explainable AI.
- Understand challenges in developing explainable systems.
Practical Applications and Advanced Case Studies
- Conduct in-depth studies in healthcare, finance, and retail.
- Draw lessons from industry-specific AI applications.
- Review and synthesize knowledge from course projects.
- Share group observations and applications of learned concepts.
Prerequisites
This course assumes a basic knowledge of AI concepts.
Materials
Required (student must provide)
- Laptop
Provided (student will receive)
- Downloadable course materials
Who Should Attend
This course is ideal for professionals with foundational AI knowledge, including engineers, data scientists, and military personnel seeking to deepen their understanding of AI's cognitive processes as well as decision-making and ethical implications in real-world applications.
What You Will Learn
- Neural network architectures and learning processes
- Advanced ML techniques, including ensemble methods and reinforcement learning
- Development and enhancement of AI models using Python and Jupyter notebooks
- Real-world applications from medical imaging to autonomous vehicles
- Implementation of advanced data preprocessing and handling techniques
- Exploration of decision-making mechanisms and their applications in AI
- Ethical considerations in AI deployment
How You Will Benefit
- Build and fine-tune sophisticated AI systems that replicate human cognitive abilities.
- Gain practical experience with Python and Jupyter notebooks in AI development.
- Enhance your ability to process and analyze complex data for improved decision-making.
- Apply your skills in diverse industries, improving outcomes in healthcare, transportation, and security.
- Navigate ethical challenges in AI, ensuring responsible and equitable technology use.
- Prepare for future advancements in AI with a strong foundation in current methodologies and applications.
- Leverage AI capabilities to drive innovation and efficiency within your organization.
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Grow Your Professional Network
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Taught by Experts in the Field
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GTPE does not have a discount program for senior citizens. However, Georgia Tech offers a 62 or Older Program for Georgia residents who are 62 or older and are interested in taking for credit courses. This program does not pay for noncredit professional education courses. Visit the Georgia Tech Undergraduate Admissions page for more information on the undergraduate program and the Georgia Tech Graduate Admissions page for more information on the graduate program.
GTPE does not have a program for senior citizens. However, Georgia Tech offers a 62 or Older Program for Georgia residents who are 62 or older and are interested in taking for credit courses. This program does not pay for noncredit professional education courses. Visit the Georgia Tech Undergraduate Admissions page for more information on the undergraduate program and the Georgia Tech Graduate Admissions page for more information on the graduate program.
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