Ai Fundamentals: Core Concepts And Theories For Beginners

Your Beginner’s Guide to the Fundamentals of Artificial Intelligence

What you'll learn

Understand the impact of data quality on machine learning model performance

Learn how data quantity influences AI accuracy and reliability

Explore techniques for effective data collection and preprocessing

Evaluate the importance of balanced datasets for successful AI applications

Requirements

Basic Computer Literacy: Familiarity with using a computer and navigating the internet

Interest in AI: A curious mindset and eagerness to learn about Artificial Intelligence concepts

No Coding Knowledge Required: This course is theoretical and does not require programming skills

High School Mathematics: Basic understanding of linear algebra and probability will be helpful but is not mandatory

Description

Unlock the mysteries of Artificial Intelligence (AI) with this comprehensive, theory-focused course. Designed for beginners and enthusiasts, this course dives deep into the foundational principles, methodologies, and frameworks driving modern AI technologies. Whether you’re a student, professional, or simply curious about AI, this course will help you build a strong conceptual understanding of AI without requiring coding knowledge.What You’ll Learn:The core concepts and history of AI, from Alan Turing to modern advancements.Types of AI: Narrow AI, General AI, and Superintelligence.Machine Learning principles: Supervised, Unsupervised, and Reinforcement Learning.The mathematical foundations of AI, including linear algebra and probability.The bias-variance tradeoff, overfitting, and techniques to improve model performance.The critical role of data quality and quantity in machine learning.Applications of AI in industries such as healthcare, finance, and transportation.The ethical, societal, and philosophical implications of AI.Who This Course is For:Beginners curious about Artificial Intelligence concepts.Non-technical professionals who want to understand AI theory.Students and researchers seeking a strong foundation in AI theory.Enthusiasts eager to explore the societal and philosophical aspects of AI.What Makes This Course Unique:No Coding Required: Focus entirely on theory and concepts without diving into programming.Comprehensive Coverage: Explore AI’s history, methodologies, applications, and ethical considerations.Practical Insights: Learn how AI is transforming industries through real-world examples.Accessible Content: Complex theories simplified for easy understanding.Why Take This Course?AI is reshaping our world, and understanding its principles is key to staying ahead in today’s technology-driven landscape. By the end of this course, you will have the knowledge and confidence to discuss AI concepts and their implications in academic, professional, or casual settings.Enroll now and take the first step toward mastering the fascinating world of Artificial Intelligence!

Overview

Section 1: Module 1: Introduction to Artificial Intelligence

Lecture 1 Understand the core concepts and history of AI

Lecture 2 Lesson 2: Brief History of AI: From Turing to Modern AI

Lecture 3 Lesson 3: Types of AI: Narrow, General, and Superintelligence

Lecture 4 Lesson 4: Key Applications of AI in the Real World

Section 2: Module 2: Core Concepts in AI

Lecture 5 Lesson 1: Machine Learning (ML): Types and Overview

Lecture 6 Lesson 2: Knowledge Representation and Reasoning

Lecture 7 Lesson 3: Problem Solving and Search Algorithms

Lecture 8 Lesson 4: Decision Making in AI Systems

Section 3: Module 3: Machine Learning Theory

Lecture 9 Lesson 1 Outline Supervised, Unsupervised, and Reinforcement Learning

Lecture 10 Lesson 2: Mathematical Foundations of ML: Linear Algebra and Probability

Lecture 11 Lesson 3: Bias-Variance Tradeoff and Overfitting

Lecture 12 Lesson 4: The Role of Data in ML: Quality and Quantity

Beginners Curious About AI: Individuals who want to explore Artificial Intelligence concepts without diving into coding,Non-Technical Professionals: Business professionals, managers, or decision-makers looking to understand AI's potential,Students and Researchers: Those seeking a strong theoretical foundation in AI for academic or professional pursuits,AI Enthusiasts: Anyone interested in learning about AI's principles, applications, and societal impact