Machine Learning & Artificial Intelligence - A simplified Approach

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Created by Subramanya Bhat Last updated Mon, 12-Jul-2021 English
Learning objectives
  • Understand Machine Learning Algorithms.
  • Understand Mathematical concepts required to understand Machine Learning Algorithms
  • Implement Machine Learning Algorithms.
  • Implement Industry and Interdisciplinary real-time Projects.
  • Get jobs in Corporate Sectors.
  • Take up advanced Courses in Machine Learning Such as Deep Learning and Natural Language Processing.

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Course description

More importantly Machine Learning is likely to play a key role in the following sectors in India in the next decade. Defence and Security, HealthCare, Financial Market, Medical Data Analysis, Climate and Weather, Traffic and other Social Issues related to Big Data. We have found that one of the primary needs for all is to Sensitize, Nurture and Grow next generations of youngsters capable of using Machine Learning Techniques. This can best be done by Preparing and Capacity building of existing and new students and Professionals into this domain. This is the way IT domains were created earlier.

Topics such as decision trees, statistics, Linear Regression, Pattern Recognition, K-Nearest Neighbourhood, Support Vector Machine etc are covered. The training is expected to train students and Professionals Machine Learning techniques for specific application and integrates possibility of extending the techniques to new applications of present day technological advancement.

In the course all concepts are shown with Python Implementations. Students and Professionals are trained with Lab sessions. They are given with Laboratory exercises and real-time projects and they can get jobs in the corporate sector easily.

Eligibility criteria
  • • Pursuing/completed Diploma / Engineering in all streams of Engineering
  • • Working Professionals in Industry for uplifting their career in Machine Learning, Artificial Intelligence

Curriculum
12 Lessons 06:26:46 Hours
Module 1-Introduction to Machine Learning,
4 Lessons 02:32:45 Hours
  • Introduction to Machine Learning, Different Types of Learning 00:41:45
  • Decision Trees, Overfitting and underfitting 00:41:00
  • Decision Trees, Linear Regression 00:40:30
  • Python Exercises on Decision Trees and Linear Regression 00:29:30
  • Mean, standard Deviation, eigen values, eigen vectors, Principal Component Analysis 00:41:00
  • Independent Component Analysis, KNN algorithm 00:27:50
  • KNN Algorithm Implementation using python, Logistic Regression (Module 3) 00:27:05
  • Support Vector Machine, Non Linear SVM, Python Exercises 00:04:06
  • Artificial Neural Networks 00:42:30
  • Python Exercises 00:36:50
  • Performance Measures of Machine Learning algorithms 00:25:00
  • Performance Measures and Projects 00:29:40
  • MCQ Question
Rs 1999 Rs 10000
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Includes:
  • 06:26:46 Hours On demand videos
  • 13 Lessons
  • Access on mobile and tv
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Trainer profile
About:

Bhat has published12 papers in the International & National Journals, 18 papers International & National Conferences all over India. Published papers in peer reviewed journals like Elesvier, Springer and Inderscience.  Also published 02 book chapters in Springer.

 

He is a reviewer for international Journals and conferences. He delivered many technical talks in the area of signal processing, power electronics and Image processing.

 

His areas of interests are Signal processing, Power Electronics and Machine Learning.

 

During his career he interacted with Eminent professors Dr. B K Bose University of Tennessee, UAS. Dr. Ashoka K S Bhat, Victoria University, Dr. Vittal Rao, Professor, IISc, Dr. Ashok Rao, Former Head-Network project Head IISC Bengaluru and Late Dr. R D Sudhaker Samuel, Former Professor & Head, Department of Electronics & Communication Engineering, Sree Jayachamarajendra College of Engineering, Mysuru.

  Bhat is a committed, dedicated, transparent and highly disciplined person, from an orthodox family, who opted teaching profession as a choice. He has the passion towards serving the needy people. He feels that serving for the student community is more precious than his own family. He is of the opinion that, anything and everything can be achieved through discipline.

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