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Artificial Intelligence

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In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans.

1. To have an appreciation for and understanding of both the achievements of AI and the theory underlying those achievements. To have an appreciation for the engineering issues underlying the design of AI systems.


2. To have a basic proficiency in a traditional AI language including an ability to write simple to intermediate programs and an ability to understand code written in that language.


3. To have an understanding of the basic issues of knowledge representation and blind and heuristic search, as well as an understanding of other topics such as minimax, resolution, etc. that play an important role in AI programs.


4. To have a basic understanding of some of the more advanced topics of AI such as learning, natural language processing, agents and robotics, expert systems, and planning.

  • Strong hold on Mathematics

  • Strong experience of programming languages

  • Writing algorithm for finding patterns and learning

  • Strong data analytics skills

  • Good knowledge of Discrete mathematics

  • Strong will to learn machine learning languages

Pc or Laptop



Course Outline


1. Introduction to Machine learning
2. Supervised learning
3. Unsupervised learning
4. Reinforcement learning Scikit-learn API, Linear regression and Case studies
5. Introduction to Deep Learning
6. Use cases and application
7. Implications of deep learning and mobility
8. ANN with hidden layers
9. Activation function options
10. Linear versus non-linear functions
11. Available libraries to work with(TensorFlow, Keras, TFLearn)
12. CNN concepts
13. Image classification using CNN
14. Introduction to Neural Networks
15. Multi-layered Neural networks
16. Training of neural networks
17. DNN: Deep Neural Networks
18. CNN: Convolutional Neural Networks
19. RNN: Recurrent Neural Networks
20. Introduction to AI
21. Data Processing and feature engineering
22. Natural language processing
23. Popular search algorithms
24. Fuzzy logic system

Pricing



Free


  • 1 Live/Recorded Session
  • Two Sample Modules PDF
  • Free Reference Ebook
  • Course Content
  • Senior Trainer
  • Interactive Learner Dashboard
  • Sample Module Quiz
  • Online Test
  • 24X7 System Support



Choose Plan

Silver

$100 $200

  • Fresher(Basic Course )
  • 10 Modules
  • 10 Lab Sessions
  • Course Content
  • Senior Trainer
  • Interactive Learner Dashboard
  • 10 Module Quiz
  • Online Test and Certificate
  • Learner Progress Report
  • 24X7 System Support


Choose Plan

Gold

$150 $300

  • Intermediate (Advance Course)
  • 20 Modules
  • 20 Lab Sessions
  • Course Content
  • Senior Trainer
  • Interactive Learner Dashboard
  • 20 Module Quiz
  • Online Test and Certificate
  • Learner Progress Report
  • 24X7 System Support


Choose Plan

Diamond

$250 $500

  • Expert Level(Project Oriented)
  • 30 Modules
  • 30 Lab Sessions
  • Course Content
  • Senior Trainer
  • Interactive Learner Dashboard
  • 30 Module Quiz
  • Online Test and Certificate
  • Learner Progress Report
  • Live Project Guidance
  • Discussion Forum
  • 24X7 System Support
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