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  • Introduction to AI 2-week

Introduction to AI 2-week

  • By Kushawaha Shankar
  • Artificial Intelligence
  • (0 Rating)
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    • πŸ“… WEEK 1: AI Fundamentals & Core Concepts

      Day 1: Introduction to Artificial Intelligence

      • What is Artificial Intelligence?

      • History & evolution of AI

      • Human Intelligence vs Machine Intelligence

      • Types of AI:

        • Narrow AI

        • General AI

        • Super AI

      • Myths & facts about AI

      Activity: Identify AI used in daily life (Google, Alexa, Netflix)


      Day 2: How AI Works

      • Basic AI workflow:

        • Data β†’ Algorithm β†’ Model β†’ Prediction

      • Role of data in AI

      • Introduction to algorithms

      • AI vs Automation vs Programming

      Activity: Simple AI workflow diagram


      Day 3: Introduction to Machine Learning

      • What is Machine Learning?

      • Types of ML:

        • Supervised Learning

        • Unsupervised Learning

        • Reinforcement Learning

      • Examples:

        • Spam detection

        • Recommendation systems


      Day 4: Deep Learning Basics

      • What is Deep Learning?

      • Neural Networks (simple idea)

      • Human brain vs Artificial Neural Network

      • Applications of Deep Learning

      Demo: Image recognition example (Google Teachable Machine)


      Day 5: AI Tools & Platforms

      • Popular AI tools:

        • ChatGPT

        • Google Teachable Machine

        • DALLΒ·E / Image generators

      • AI in education, healthcare, business

      • No-code AI platforms overview

      Hands-on: Create a simple AI model using Teachable Machine


      πŸ“… WEEK 2: AI Applications, Ethics & Mini Project

      Day 6: Natural Language Processing (NLP)

      • What is NLP?

      • How machines understand language

      • Applications:

        • Chatbots

        • Voice assistants

        • Translation tools

      Activity: Chatbot interaction analysis


      Day 7: Computer Vision

      • What is Computer Vision?

      • Image vs Video processing

      • Face detection & object detection

      • Real-world examples:

        • CCTV

        • Self-driving cars

      Demo: AI image recognition tool


      Day 8: AI Ethics & Future of AI

      • Ethical issues in AI:

        • Bias

        • Privacy

        • Job impact

      • Responsible AI

      • Future trends in AI

      • AI career paths

      Discussion: Can AI replace humans?


      Day 9: Mini AI Project (Implementation)

      Project Options (choose one):

      1. AI Image Classifier

      2. AI Chatbot (No-code tool)

      3. AI Voice Recognition Demo

      4. AI Recommendation Concept

      • Problem statement

      • Tool selection

      • Model training

      • Testing & improvement


      Day 10: Project Presentation & Assessment

      • Project demonstration

      • Explanation of AI concept used

      • Viva / Q&A

      • Feedback & improvement tips


      πŸ“˜ Assessment & Evaluation

      • Quiz (MCQs & True/False)

      • Mini Project (40%)

      • Participation (20%)

      • Final Presentation (40%)

      Show More
      What Will You Learn?
      • You learn Artificial intelligence from Basic

      Material Includes

      • 1. Students will learn Artificial Intelligence From Basic
      • 2. Students will get Internship certificate

      Requirements

      • A Laptop with good internet connection

      Audience

      • Students

      Course Content

      Week 1
      In Week 1, learners are introduced to the fundamentals of Artificial Intelligence (AI) and its growing impact on modern technology. The week begins by explaining what AI is, its history, and how it differs from traditional programming. Key concepts such as intelligent agents, environment types, and rational behavior are discussed to build a strong conceptual foundation. Students explore the main branches of AI, including machine learning, natural language processing, computer vision, and robotics, with real-world examples to understand their applications. The course also covers types of AIβ€”narrow AI, general AI, and super AIβ€”highlighting current capabilities and future possibilities. By the end of Week 1, learners gain a clear understanding of how AI systems work, where AI is used in daily life, and the ethical considerations and limitations of AI. This week prepares students with essential knowledge required for the practical and advanced topics introduced in Week 2.

      • Artificial Intelligence Syllabus Discussion and Analysis
        11:26
      • What’s the FUTURE of Artificial Intelligence
        04:30
      • Quiz on What’s the FUTURE of Artificial Intelligence.
      • What is Artificial Intelligence | Learn AI with Real Life Examples
        08:30
      • Quiz on What is Artificial Intelligence | Learn AI with Real Life Examples
      • What is State Space Search | Introduction to Problem Solving in Artificial Intelligence
        10:47
      • Quiz on What is State Space Search | Introduction to Problem Solving in Artificial Intelligence
      • Uninformed Vs Informed Search in Artificial Intelligence with Example
        08:17
      • Quiz on Uninformed Vs Informed Search in Artificial Intelligence with Example

      Week 2
      Week 2 focuses on the problem-solving and search techniques in Artificial Intelligence, building on the foundational concepts introduced in Week 1. This week helps learners understand how AI systems make decisions and find solutions to complex problems. The week begins with an introduction to problem formulation, where real-world problems are represented using state space, initial state, goal state, and actions. Learners study State Space Search as a core AI approach for systematically exploring possible solutions. Students then explore search strategies, divided into uninformed (blind) search and informed (heuristic) search. Algorithms such as Breadth-First Search (BFS), Depth-First Search (DFS), and Uniform Cost Search (UCS) are discussed, followed by heuristic-based methods like Greedy Best-First Search and A* Search. Real-life examples such as maze solving, route planning, and puzzle problems help connect theory with practical applications. The week also highlights the importance of heuristics, efficiency, and optimality in search, along with a comparison of different algorithms based on time and space complexity. By the end of Week 2, learners gain a clear understanding of AI problem-solving techniques, enabling them to analyze problems, choose appropriate search strategies, and appreciate how intelligent systems find efficient solutions in real-world scenarios.

      • Informed vs Uninformed vs Adversarial Search With Examples
        06:22
      • Quiz on Informed vs Uninformed vs Adversarial Search With Examples
      • Breadth First Search (BFS) with example | Uninformed Search
        12:56
      • Quiz on Breadth First Search (BFS) with example | Uninformed Search
      • Depth First Search (DFS) with example | Uninformed Search
        09:12
      • Quiz on Depth First Search (DFS) with example | Uninformed Search
      • Time & Space Complexity of BFS and DFS
        07:57
      • Quiz on Time & Space Complexity of BFS and DFS
      • Bidirectional Search Algorithm in Artificial Intelligence in Hindi with Real Life Examples
        08:47
      • Quiz on Bidirectional Search Algorithm in Artificial Intelligence in Hindi with Real Life Examples

      A course by

      Kushawaha Shankar
      Kushawaha Shankar
      CAD CAM developer.

      Student Ratings & Reviews

      No Review Yet
      No Review Yet

      Course Includes:

      • Price:
        ₹800.00 Original price was: ₹800.00.₹249.00Current price is: ₹249.00.
      • Instructor:Kushawaha Shankar
      • Duration: 15 hours
      • Lessons:10
      • Students:2
      • Level:All Levels
      ₹249.00 ₹800.00
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