Compare types of decision making and thinking with a focus on emotional versus logical and literal versus abstract.
Describe types of machine learning (ML).
Describe the challenges and limitations of artificial intelligence (AI) systems.
Compare and contrast AI, ML, and deep learning (DL).
Differentiate between the major branches of AI (ML, neural networks, expert systems, natural language processing, robotics, and fuzzy logic).
Examine the role of AI in software.
Examine the role of AI in software and physical systems.
Explain how computers model intelligent behavior (as found in robotics, speech and language recognition, and computer animation).
Test a machine-learning algorithm using human input data.
Write a machine-learning algorithm.
Hypothesize the future of technology and technology-related careers.
Categorize careers by the role of computing.
Explain the impact of computing on 21st-century careers.
Describe careers created by innovation in computing and technology.
Describe careers to which computing is central.
Recognize the role of computing in a wide spectrum of careers.
answer them in very very small short sentences
Types of decision making include emotional (based on feelings) and logical (based on reasoning). Types of thinking include literal (taking things at face value) and abstract (thinking creatively or outside the box).
Machine learning (ML) involves algorithms that enable computers to learn and make predictions from data without being explicitly programmed.
Challenges and limitations of artificial intelligence (AI) systems include ethical issues, biases in algorithms, and the potential for job displacement.
AI involves machines that can perform tasks that typically require human intelligence, while ML focuses on algorithms that enable machines to learn from data. Deep learning (DL) is a subset of ML that uses neural networks to simulate human-like decision-making.
Major branches of AI include ML, neural networks, expert systems, natural language processing, robotics, and fuzzy logic.
AI plays a role in software development by enabling programs to automate tasks, make predictions, and improve user experience.
AI also plays a role in physical systems like autonomous vehicles, medical devices, and smart home technology.
Computers model intelligent behavior through techniques like machine learning, using algorithms to analyze data and make decisions in areas like robotics, speech recognition, and computer animation.
Testing a machine-learning algorithm involves providing it with human input data to evaluate its performance and accuracy.
Writing a machine-learning algorithm involves coding instructions for a computer to learn from data and make predictions or decisions.
The future of technology and technology-related careers is likely to involve advancements in AI, automation, and data analytics.
Careers can be categorized by the role of computing, such as software development, data analysis, cybersecurity, and AI research.
Computing has had a significant impact on 21st-century careers by creating new job opportunities, transforming industries, and requiring digital skills in various fields.
Innovation in computing and technology has created new careers in areas like virtual reality, cybersecurity, digital marketing, and tech entrepreneurship.
Computing is central to careers in fields like software engineering, data science, artificial intelligence, and computer programming.
Computing plays a role in a wide spectrum of careers, from healthcare and finance to entertainment and transportation, as technology continues to shape the future of work.