This course introduces the fascinating world of Artificial Intelligence (AI) to beginners, offering a solid foundation in AI concepts, tools, and real-world applications. By the end of this course, learners will have a clear understanding of AI principles, basic machine learning techniques, and how AI is transforming industries. This course will demystify AI and prepare learners for more advanced AI and machine learning topics.
Target Audience:
- Beginners in AI: Individuals with little to no background in AI or data science who are eager to learn.
- Tech Enthusiasts: People interested in understanding how AI works and how it is shaping the future.
- Professionals in Non-Tech Fields: Individuals from various industries who want to understand AI’s potential applications in their fields.
- Students and Educators: Those looking for a foundational understanding of AI.
Learning Objectives:
By the end of this course, learners will be able to:
- Understand the core concepts of AI, including machine learning, neural networks, and natural language processing (NLP).
- Identify the differences between AI, machine learning, and deep learning.
- Understand real-world applications of AI in industries such as healthcare, finance, and marketing.
- Develop a basic understanding of how AI models are built and trained.
- Explore ethical considerations and the future implications of AI in society.
- Use basic AI tools and platforms to experiment with simple AI projects.
Course Modules:
Module 1: Introduction to AI
- Lesson 1: What is AI? A Historical Perspective
- Lesson 2: AI vs. Machine Learning vs. Deep Learning
- Lesson 3: Real-World AI Applications Across Industries
Module 2: Core Concepts of AI
- Lesson 1: Data: The Foundation of AI
- Lesson 2: Algorithms: How Machines Learn
- Lesson 3: Neural Networks Explained Simply
Module 3: Tools and Platforms for AI
- Lesson 1: Introduction to Python for AI
- Lesson 2: Overview of Popular AI Tools (Google AI, Microsoft AI, IBM Watson)
- Lesson 3: Building Your First AI Model with No-Code Platforms
Module 4: Machine Learning Basics
- Lesson 1: Supervised vs. Unsupervised Learning
- Lesson 2: Training Models with Data
- Lesson 3: Evaluating Model Performance
Module 5: Ethical Considerations and Future of AI
- Lesson 1: Ethics in AI: Bias, Privacy, and Accountability
- Lesson 2: AI and the Job Market: Threat or Opportunity?
- Lesson 3: The Future of AI: Trends and Innovations
Target audiences
- Beginners in AI: Individuals with little to no background in AI or data science who are eager to learn.
- Tech Enthusiasts: People interested in understanding how AI works and how it is shaping the future.
- Professionals in Non-Tech Fields: Individuals from various industries who want to understand AI’s potential applications in their fields.
- Students and Educators: Those looking for a foundational understanding of AI.