Is data science going to be obsolete?

Data scientists are unlikely to become obsolete until we get a rise of Artificial General Intelligence, that is, AI with general abilities.

Will AutoML be the end of data scientists?

Will AutoML replace data scientists? The short answer is yes. While AutoML can carry some of the machine learning workflow without the need for data scientists, that doesn’t mean the data science skill set will become obsolete.

Do data scientists need machine learning?

Machine learning is not the answer to every data scientist’s problem. But not every “data science” problem requires a machine learning model. In some cases, a simple analysis with Excel or Pandas is more than enough to solve the problem at hand.

What is the future of data scientists?

You can think about the data increase from IoT or from social data at the edge. If we look a little bit more ahead, the US Bureau of Labor Statistics predicts that by 2026—so around six years from now—there will be 11.5 million jobs in data science and analytics.

Will AutoML replace machine learning?

When taking on these responsibilities, data scientists can use automation options for some parts of a machine learning process. But, AutoML cannot fully replace these responsibilities of a data scientist.

Will machine learning get automated?

Machine learning can be automated when it involves the same activity again and again. However, the fundamental nature of machine learning deals with the opposite: variable conditions. In this regard, machine learning needs to be able to function independently and with different solutions to match different demands.

Should I learn deep learning as a data scientist?

With Deep Learning being seen as the place where machine learning advances are coming for the present, it is often recommended that beginning data scientists need to learn how deep learning works as an essential step towards establishing a deep learning career.