Course Content

Course Content


Familiarity with programming languages such as Python, SQL, and Java; hypothesis testing; data modelling; and proficiency in mathematics, probability, and statistics (such as Naive Bayes classifiers, conditional probability, and likelihood) are just a few of the data science fundamentals that machine learning engineers rely on.

Yes, if you're interested in data, automation, and algorithms, machine learning is a terrific career path for you. Your day will be filled with evaluating enormous amounts of data and implementing and automating it.

Yes, if you want to work in artificial intelligence or machine learning, you'll need to know how to code.

Machine learning engineers are typically required to have a master's degree in computer science or a related subject, and in certain cases, a Ph. D. A machine learning engineer's background must include advanced mathematical knowledge and data analytical skills.

Learning machine learning will take anywhere from 3 months to 6 years, depending on your present education and experience in programming, statistics, and data science. Machine learning is a subset of AI that generates predictions and judgments based on data inputs, algorithm execution, and feedback loops.

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