|This course covers an overview of Artificial Intelligence,Machine Learning system, components and functions. Introduction to supervised, non supervised and Deep learning algorithms. Basic mathematics around the algorithms, reference implementations, assignments that would enable implement customer solutions. Basics of python programming, libraries associated to ML like NUMPY, PANDAS, SciLearn. Knowledge Searching and inference using AI Techniques, Robot Motion planning, Reinforced learning, Fuzz logic and expert system|
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- Components of Machine Learning system – Features and Functions.
- Significance of Data-set, Basics of the Algorithm design.
- Algorithm selections for real life solutions.
- Scope of AI, techniques to represent knowledge and learning.
- Hands on assignment for each algorithm.
- Internship with hands-on real time project.
- Lectures 11
- Quizzes 0
- Duration 96 hours
- Skill level All level
- Language English
- Students 0
- Assessments Yes