Data Analysts work with datasets such as numbers, facts, and figures, to analyze them and find conclusions. Their job responsibility also calls for translating complex data into simple and understandable documents, extracting data, coding, designing and developing algorithms, and more. Data Analysts are expected to possess analytical skills, eye for details, mathematic skills, and interpretation skills.
Data engineers are responsible for evaluating the quality and accuracy of the datasets. Some of the programming languages include MongoDB, NoSQL, SQL, Cassandra, and more. Their job profile also involves developing the key business questions and building datasets for the solutions to those questions.
ML Engineer profile demands familiarity with Python, C++, Java, Scala, JavaScript, etc. They are responsible for creating algorithms which are used for decoding the patterns collected from larger datasets. Other responsibilities of Machine Learning Engineers involve designing and implementing applications/algorithms likeanomaly detection, predictions, classification, etc.
Data Scientists are professionals who are analytical data experts with skills in solving complex problems. It is a highly demanded job profile. Data Scientists also deciphers through large datasets to decode the insight and built designs using fierce mathematic skills, programming skills, and statistic skills to decode and structure them.
The revolution of Machine Learning (ML) is based on the idea that machines can function on its own without any human intervention or assistance when it is provided with data.The marathon of Artificial Intelligence (AI) has begun to captain the modern world economy and many top international universities have started to incorporate AI as an academic subject. This only means that in order to a formidable leader in the future it is vehement to possess the knowledge of Machine Learning.