Machine Learning

In this course, understand Machine Learning techniques and practise using wide variety of datasets.Process, clean, visualize and analyse data using Python or R programming.  We accommodate beginners in R or Python and help them grasp in-demand Machine Learning techniques. Post completion of this course, you can automate decision making and build web-based machine learning applications. 


  • Supervised Learning
  • Build supervised machine learning models to make data-informed decisions. Evaluate and validate the model quality.

  • Unsupervised Learning   

  • Build unsupervised machine learning models and use data processing techniques such as scaling and PCA.

Key Features

  • Analyze data using Machine Learning Techniques
  • Solve and Practice over 10+ Business use cases
  • Master skills from Industry Consultants and Practitioners
  • Grow your analytics skills

What you learn?

  • Introduce Machine Learning
  • Manage and Understand Data
  • Apply Nearest Neighbours Classification
  • Apply Naive Bayes
  • Apply Decision Trees and Classification Rules
  • Apply Regression Trees and Model Trees
  • Apply Neutral network and Support Vector Machine
  • Apply Association Rules
  • Apply Clustering
  • Evaluate and improve model performance

What you get?

  • Pure Practical Live Environment Set up
  • Classroom session with Experts
  • Doubt-clearing sessions and assignment review
  • Master high in-demand programming skills
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