The boundaries between Machine Learning, Artificial Intelligence, and Data Science are not exactly clear-cut. Without a clear understanding of the differences, many find themselves starting at the wrong spot and quickly getting discouraged by the complexity of it all.
Data Science requires a wide range of skills in math/statistics, programming, and domain knowledge of the field of application.
Machine Learning refers to the ability of a computer program to learn or improve performance without explicit programming. Machine learning is used by Data Scientists for data analysis and interpretation. Software Engineers rely on Data Science tools and techniques to prepare data for use in ML.
Artificial Intelligence is described as a machine’s capability to replicate the intellectual capabilities of the human mind. AI uses machine learning techniques as well as expert systems or intelligent search.
Both Data Science and AI use Machine Learning as a key tool. In Data Science, Machine Learning is applied as a data analysis tool to identify patterns in data and make predictions. In AI, Machine Learning aids in the development of intelligent agents. Intellipaat is offering a Data Science Online Course. You can Enroll in this and start learning from anywhere.
Ultimately, if your foundation and understanding of data are weak, then you will find all these three domains to be equally difficult. So, a strong knowledge of data processing, cleaning, analyzing, and visualization, along with statistical foundations, will serve you well no matter which of the three fields you choose.
Learn about the difference between Machine Learning and AI from this video by Intellipaat.
Back