Artificial Intelligence For Engineering (KMC101/KMC201)

Artificial Intelligence For Engineering (KMC101/KMC201)

Artificial Intelligence For Engineering (KMC101/KMC201)

Course Objective

The students will be able to:

  • Understand the evolution and various approaches of AI
  • Understand data storage, processing, visualization, and its use in regression, clustering, etc.
  • Understand natural language processing and chatbots
  • Understand the concepts of neural networks
  • Understand the concepts of face, object, speech recognition, and robots

Lessons

  1. Unit 1 - An overview to AI

    1. The evolution of AI to the present

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    2. Various approaches to AI

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    3. What should all engineers know about AI?

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    4. Other emerging technologies

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    5. AI and ethical concerns

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    prutor.ai
  2. Unit 2 - Data & Algorithms

    1. History Of Data

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    2. Data Storage And Importance of Data and its Acquisition

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    3. The Stages of data processing

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    4. Data Visualization

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    5. Regression, Prediction & Classification

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    6. Clustering & Recommender Systems

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    prutor.ai
  3. Unit 3 - Natural Language Processing

    1. Speech recognition

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    2. Natural language understanding

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    3. Natural language generation

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    4. Chatbots

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    5. Machine Translation

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    prutor.ai
  4. Unit 4 - Artificial Neural Networks

    1. Deep Learning

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    2. Recurrent Neural Networks

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    3. Convolutional Neural Networks

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    4. The Universal Approximation Theorem

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    5. Generative Adversarial Networks

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    prutor.ai
  5. Unit 5 - Applications

    1. Image and face recognition

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    2. Object recognition

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    3. Speech Recognition besides Computer Vision

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    4. Robots

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    5. Applications

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    prutor.ai