About Course
This course provides a foundational understanding of Artificial Intelligence (AI), its core concepts, applications, and ethical considerations. Learners will explore machine learning, deep learning, and natural language processing (NLP) with hands-on projects.
Course Content
Module 1: Introduction to Artificial Intelligence
Summary:
This module introduces the fundamentals of AI, including its history, evolution, and key concepts. Learners will explore the differences between AI, Machine Learning (ML), and Deep Learning (DL) and understand real-world applications in industries like healthcare, finance, and robotics.
Key Takeaways:
What AI is and how it works
AI vs. Machine Learning vs. Deep Learning
AI applications in daily life
Summary:
This module introduces the fundamentals of AI, including its history, evolution, and key concepts. Learners will explore the differences between AI, Machine Learning (ML), and Deep Learning (DL) and understand real-world applications in industries like healthcare, finance, and robotics.
Key Takeaways:
What AI is and how it works
AI vs. Machine Learning vs. Deep Learning
AI applications in daily life
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Lesson 01: What is AI?
05:27 -
Lesson 2: History of AI
10:00 -
Lesson 3: AI Applications in the Real World
15:00
Module 2: Machine Learning Basics
This module covers Machine Learning (ML) fundamentals, explaining how ML algorithms learn from data to make predictions. It introduces Supervised, Unsupervised, and Reinforcement Learning and explores commonly used ML models like Linear Regression, Decision Trees, and K-Nearest Neighbors (KNN).
Key Takeaways:
Understanding different types of ML algorithms
How machines learn from data
Hands-on project: Building a basic ML model
Key Takeaways:
Understanding different types of ML algorithms
How machines learn from data
Hands-on project: Building a basic ML model
Final Quiz
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