Machine Learning Workshops

END to END Supervised Learning

About the workshop

This is a two day workshop which will progressively take you through what is Machine Learning and what are the practical applications and fields in which machine learning is applied. You will also get the introduction to Supervised Machine Learning and hands-on experience on applying it to titanic problem taken from Kaggle. At the end of this workshop, you would have solved and uploaded your results to the Kaggle site.

Day 01 : Introduction To Machine Learning

This session of the workshop provides what is Machine Learning all about and what are the various applications of machine learning. This also provides a path on where to start for establishing a career in machine learning and the process that has to be followed to make predictions on a machine learning problem.

Day 02 : Supervised Machine Learning

Supervised Learning is the type of machine learning problem where the model is trained on a predefined data set which has target values specified. This workshop provides the process that has to be followed to solve a supervised machine learning problem and also a hands-on experience on titanic problem taken from Kaggle.

Key takeaways

Recognizing the problem

A high level overview of what machine learning is and to recognize the problems that can be solved with Machine Learning.

Selecting the techniques

Select the right technique to solve the problem (is it a classification problem? a regression? needs preprocessing?).


A few libraries like Numpy, Pandas, Scikit-Learn, to start your learning experience, that you can improve upon.


A certificate for succesful completion of the course.


Finally, you would be able to decide if Machine Learning is for you and what you would have to do next, if you want to make this your career.


  • Having a good knowledge of programming concepts (writing loops, data structures, functions and recursive functions).
  • Knowledge of Python. (If you are not sure about your knowledge of python, sign up for the Basic Python for Data Science course).
  • Laptop with Wifi capability and Python 3.x installed.
  • A desire and thirst for knowledge.