Course Content

Course Content

FAQs

The professional path of a Data Scientist can be divided into four categories: data, engineering, business, and product. The function of Data Scientist is diverse, and the career path along each axis can be seen as a continuation of some of these fields.

Yes, data science is a great professional path with a lot of room for progress in the future. Demand is already strong, compensation are competitive, and benefits are plentiful, which is why LinkedIn has named Data Scientist "the most promising career" and Glassdoor has named it "the finest job in America."

Data analysis, for instance, necessitates a basic understanding of descriptive statistics and probability theory. These ideas will assist you in making better data-driven business decisions. Probabilistic distributions, statistical significance, hypothesis testing, and regression are all important topics to understand.

  • Data Analyst. Role.
  • Data Scientist.
  • Machine Learning Engineer.
  • Machine Learning Scientist.
  • Applications Architect.
  • Data Architect.
  • Enterprise Architect.
  • Infrastructure Architect.

The answer is an unequivocal YES! Demand for Data Scientists is on the rise all around the world, and the lack of competition for these positions makes data science an extremely lucrative career choice.

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