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Course Objectives :
Course Objectives :
At the end of the course the student will be able to:
Gain a historical perspective of AI and its foundations.
Become familiar with basic principles of AI toward problem solving.
Familiarize with the basics of Machine Learning & Machine Learning process, basics of Decision Tree, and probability learning
Understand the working of Artificial Neural Networks and basic concepts of clustering algorithms
About the Faculty
About the Faculty
Mrs. Ragini Krishna, Assistant Professor, Department of Information Science and Engineering, Sri Krishna Institute of Technology Bangalore. I have 12 Years of Teaching Experience and 2 years of industry experience and 5 years of research experience. I have the experience of being coordinator in the VTU valuation Center for semester examinations. I was also part of practical examination allotment team to allot practical exam duties to faculties across Bangalore Zone during the 2015 - 2016. I am persuing my Ph.D in the area of Social Network Analysis. I have published 3 research papers in International Journals and presented 2 papers in international conferences. My areas of Interest are Artificial Intelligence, Machine Learning, Data Mining and warehousing, algorithms and Data Structures.
Course Handout
Course Handout
2021_AIML - CourseHandout_Theory_PartA.docx
Resources for Further Exploration:
Resources for Further Exploration:
https://www.kdnuggets.com/2019/11/10-free-must-read-books-ai.html
https://www.udacity.com/course/knowledge-based-ai-cognitive-systems--ud409
https://www.javatpoint.com/history-of-artificial-intelligence
https://www.tutorialandexample.com/problem-solving-in-artificial-intelligence
https://www.javatpoint.com/unsupervised-artificial-neural-networks
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