Recommender Systems have become essential in personalized education information for students, as they provide relevant and useful information to students regarding specific program information and its attributes. With the rapid growth and improvement in the machine learning algorithm, the recommender systems help in finding a program that helps further in better job prospects. The system can perform more efficiently and helps in solving complex problems by using ANFIS, even with unstructured and vast datasets. In the construction of recommender systems Machine learning techniques are used which helps in academics and in the education field, discussed briefly in the research paper. 1. Relationship between Artificial Intelligence, Data Science, and Machine Learning: AI, machine learning, and data science falls in the same domain and are connected to each other. They each have their unique uses and meanings. Human intelligence is mimicked or replicated by artificial intelligence systems [1]. Systems now have the potential to automatically learn from their experiences and get better over time thanks to machine learning. Data analytics, data mining, machine learning, artificial intelligence, and several more related fields are all included under the general phrase "data science." We employ machine learning methods like supervised learning or unsupervised learning to extract predictions from the data set. To extract predictions from a given data set, machine learning techniques called supervised(managed) and unsupervised(unmanaged) learning are applied. A branch of machine learning called deep learning focuses on algorithms. Artificial neural networks are used, which are based on the composition and functionality of neurons in the human brain. When there isn't a clear data structure that you can simply exploit and create features around, deep learning is most effective. to learn from forecasts that are being made. Data analysis is performed in order to make predictions, which is actually the data science process. When data finally takes some kind of action, AI enters the scene. With the help of forecasts and insights, artificial intelligence blends automated and human decision-making to carry out tasks.