Machine Learning using Python

Out of all the technologies threatening to change the current world order, Machine Learning is the one with the most far-reaching consequences. Almost all of us have now heard the team Machine learning in some or the other context. Let us start by first defining the term.


Machine Learning is the branch of Artificial Intelligence that allows machines/systems to automatically learn from data and make decisions. As more data gathers with the machine, decisions made by the machines change to reflect that data.

Need for Machine Learning

Machine Learning has stretched the horizon of what is possible for the human race. Right from predicting weather conditions, to providing medical diagnosis, it has the potential to do the jobs which were once thought to be possible only by humans. Humans have biological limits in terms of life expectancy, memory and computation capabilities whereas for machines these resources are potentially limitless. Imagine a scenario in a country like India where qualified doctors are so scared, Machine Learning Algorithms can be exploited for diagnosing patients in remote places, suggest them appropriate medicines and perform regular checkups just like the doctor next door. This could potentially revolutionize the standard of living of people in all aspects


Machine Learning is still in its nascent stages of development. Data Scientists, engineers, analysts are working continuously towards enhancing the capabilities. The job market is badly hit by the lack of supply of engineering graduates who can develop models based on Machine Learning. The demand for such engineers has increased by 10 times in the last 5 years. It has become mandatory for all students to adapt and learn machine learning. Also, we need to empower our faculty and colleges to jump on this wave and hence help their students as well

Monkfox has recognized this opportunity and we have developed our courses to suit the needs of Colleges, Universities, Faculty and students. Our customizable Students Development Program (SDP) and Faculty Development Programs (FDP) enhance faculty and students’ knowledge about the field of and help them solve problems with real data sets.

Course Information

Estimated Time: 2 Days, 3 Days and 5 Days