Artificial Intelligence Basics

Introduction

AI Foundations

• Alan Turing and the Turing Test
• Cybernetics
• The Origin Story
• Golden Age of AI
• AI Winter
• The Rise and Fall of Expert Systems
• Neural Networks and Deep Learning
• Technological Drivers of Modern AI
• Structure of AI
• Conclusion
• Key Takeaways

Data

• Data Basics
• Types of Data
• Big Data
• Databases and Other Tools
• Data Process
• Ethics and Governance
• More Data Terms and Concepts
• Conclusion
• Key Takeaways

Machine Learning

• What Is Machine Learning?
• Standard Deviation
• The Normal Distribution
• Bayes’ Theorem
• Correlation
• Feature Extraction
• What Can You Do with Machine Learning?
• The Machine Learning Process
• Applying Algorithms
• Common Types of Machine Learning Algorithms
• Naïve Bayes Classifier (Supervised Learning/Classification)
• K-Nearest Neighbor (Supervised Learning/Classification)
• Linear Regression (Supervised Learning/Regression)
• Decision Tree (Supervised Learning/Regression)
• Ensemble Modelling (Supervised Learning/Regression)
• K-Means Clustering (Unsupervised/Clustering)
• Conclusion
• Key Takeaways

Deep Learning

• Difference Between Deep Learning and Machine Learning
• So What Is Deep Learning Then?
• The Brain and Deep Learning
• Artificial Neural Networks (ANNs)
• Backpropagation
• The Various Neural Networks
• Deep Learning Applications
• Deep Learning Hardware
• When to Use Deep Learning?
• Drawbacks with Deep Learning
• Conclusion
• Key Takeaways

Robotic Process Automation (RPA)

• What Is RPA?
• Pros and Cons of RPA
• What Can You Expect from RPA?
• How to Implement RPA
• RPA and AI
• RPA in the Real World
• Conclusion
• Key Takeaways

Natural Language Processing (NLP)

• The Challenges of NLP
• Understanding How AI Translates Language
• Voice Recognition
• NLP in the Real World
• Voice Commerce
• Virtual Assistants
• Chatbots
• Future of NLP
• Conclusion
• Key Takeaways

Physical Robots

• What Is a Robot?
• Industrial and Commercial Robots
• Robots in the Real World
• Humanoid and Consumer Robots
• The Three Laws of Robotics
• Cybersecurity and Robots
• Programming Robots for AI
• The Future of Robots
• Conclusion
• Key Takeaways

Implementation of AI

• Approaches to Implementing AI
• The Steps for AI Implementation
• Identify a Problem to Solve
• Forming the Team
• The Right Tools and Platforms
• Deploy and Monitor the AI System
• Conclusion
• Key Takeaways

The Future of AI

• Autonomous Cars
• US vs. China
• Technological Unemployment
• The Weaponization of AI
• Drug Discovery
• Government
• AGI (Artificial General Intelligence)
• Social Good
• Conclusion
• Key Takeaways