A Novel Approach for Better Career Counselling Utilizing Machine Learning Techniques

The biggest issue many students face in today's world is choosing the right career. Especially when there are so many options available to them and the counselling options available are very limited or not very efficient, Career counselling is a very essential process that assists individuals in making informed decisions about their career paths. The use of machine learning in career counselling has gained so much attention due to its potential to analyse vast amounts of data and provide personalised guidance. Previously, there had been so much work done in this field with the help of artificial intelligence and machine learning, but there was a lack of a systematic system where students could explore each and every option thoroughly and get to know what the real outcome would be if they chose that stream. In this study, various factors such as the student's interests, hobbies, past academics and performances, and achievements are taken into consideration to predict the right career option. The model is trained using five different machine learning algorithms: decision tree, Random Forest, Support Vector Machine, Nave Bayes, and K-nearest neighbours Classifier. Out of these, Random Forest gave the highest accuracy of 84.17%, and after hypertuning, it gave the highest accuracy of 85.68%. We also gave some manual inputs to the system and found out that the Random Forest gave the highest accuracy of 85.71%. The prediction results of each algorithm are summarised in this study.