Description
Artificial intelligence is the simulation of human intelligence through machines and mostly through computer systems. Artificial intelligence is a sub field of computer. It enables computers to do things which are normally done by human beings. This course is a comprehensive understanding of AI concepts and its application using Python and iPython.
The training will include the following;
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What is Artificial Intelligence?
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Intelligence
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Applications of AI
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Problem solving
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AI search algorithms
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Informed (Heuristic) Search Strategies
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Local Search Algorithms
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Learning System
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Common Sense
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Genetic algorithms
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Expert Systems
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Scikit-learn module
What is Artificial Intelligence?
The first idea of artificial intelligence was given by scientist Mr. Alan Turing around the time of the second world war. He suggested building a machine that can mimic the understanding of human intelligence and act like a human.
Artificial Intelligence today is used in all fields of work specifically banking, insurance, manufacturing, retail, logistics and so on. Its application in medical diagnosis, robots, remote sensing, etc. is a high state of the art.
AI as a subject includes the use of computer science, mathematics, statistics and domain expertise.
AI has great advantages and so of them are mentioned below:
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It provides greater precision and accuracy on detection and prediction
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Robots trained on AI can be used to do the works which are difficult for us
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AI has created newer technological breakthroughs in our life
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Fraudulent activities such as credit card transactions have become easier with AI technologies
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AI can be used in time-consuming tasks and it can save a lot of time by becoming more efficient.
You will be able to build the following as a practical project: –
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Classifiers of various types
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Logic Programming based optimizers
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Heuristic Search performed on NP-complete problems
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Natural Language Processing on text data
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Machine Learning in general for several kinds of data
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Logic and reasoning for model evaluation and interpretation
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Rule-based Programming for business use cases
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Decision Making based on AI and ML
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Stochastic methods such as time series and HMM
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