Global Online Course on Machine Learning for Cobotics

Register Now
Virtual (Microsoft Teams)
Oct 16 - Nov 15, 2021
  • Every Wednesday
    19:00 - 21:00 Hrs (IST)

  • Every Saturday
    10:00 - 13:00 Hrs. (IST)

About This Course
& Who Should Attend?

Machine Learning is an indispensable tool in advanced computing application. This course covers the elementary concepts of machine learning with illustrative case studies in the area of cobotics (collaborative robotics). The course consists of NINE lecture modules and a Team-based Online Project (TOP). This course is primarily designed for working professionals, faculty, engineering and science graduates who are working in the area of cobotics/robotics with requirements of developing data-centric algorithms.



Prof. Niladri Chatterjee

IIT Delhi, India

Dr. Rajesh Sinha

TCS, India

Dr. Pramod Gupta

UC Berkeley Extension, USA

Dr. Ravi Prakash Joshi

TechMagic K.K., Japan

Course Content

Course Content

Module 1

  • Introduction
  • What is Machine Learning and Data Mining?
  • Concepts in Machine Learning and Predictive analytics using simple problems
  • What is Predictive Analytics and Machine Learning?
  • Various Paradigms in Machine Learning
  • Steps in developing ML application
  • Application of ML
  • Introduction to Python and various packages

Module 2

  • Data Pre-processing/Feature Engineering
  • Introduction to Data pre-processing and why it is needed?
  • Various steps/techniques involved
  • Measure of Data Quality
  • Major task involved in data preparation
  • Dealing with missing values, outliers, data transformation etc.

Module 3

  • Linear Classifiers
  • Linear Regression
  • Logistic Regression
  • Linear classifiers – with practical applications

Module 4

  • Bayesian Classifiers
  • Histograms classifiers (Naïve Bayes)
  • Probability density functions
  • Class-conditional density, priors and posteriors
Module 5

  • Classifiers Contd.
  • K-nearest neighbour algorithm
Module 6

  • Decision tree and Ensemble methods
  • Decision Tree methods
  • Random Forest
Module 7

  • Unsupervised Learning
  • Clustering
  • K-means, Hierarchical Methods
  • Expectation maximization algorithm
  • Outlier and anomaly detection
Module 8

  • Feature Selection/Reduction
  • Dimension Reduction
  • Covariance Matrix
  • Feature selection and Principal component analysis
  • Regularization
Module 9

  • Performance Evaluation of Algorithms and Practical Issues
  • Evaluating and Improving Model Performance
  • Classifier performance evaluation
  • Accuracy, sensitivity, specificity, positive predictive value
  • Receiver operating characteristic
  • Cross validation Training, testing and validation
  • Applying Machine Learning Guidance and Practical Issues

Team Based Online Project

Course Fee

Registration Category Advanced Registration*

Indian Festive Offer

Students (UG/PG) 20000 INR 25000 INR
Faculty/ Industry 40000 INR 50000 INR
International Participants 800 USD 1000 USD
Last Date October 15, 2021*

October 10, 2021

October 15, 2021

*On this festive season, we are happy to announce that the GOCMLC registration date has been extended to October 15, 2021.

For crediting purposes by universities or colleges & bulk registration discounts, please contact us at Venkat@ihfc.co.in

IHFC is delighted to announce a special discount of 10% to the members of Robotics Society (TRS) , India attending the Global Online Course on Machine Learning for Cobotics

Course Flyer & Schedule

Key takeways from this course

  • Design & Develop ML algorithms for cobotic applications

  • Experiential learning with teamwork through TOP

  • Networking with domain experts, industry & peer groups

  • Get Certified : Sample certificate