Data Science and Machine Learning for Beginners: DataCamp versus the Academic Approach

Data Science, Machine Learning, and Analytics are considered to be among the hottest career paths. The demand for skilled data science practitioners in industry, academia, and government is rapidly growing. The ongoing “data rush” is therefore attracting so many professionals with diverse backgrounds such as physics, mathematics, statistics, economics, and engineering. The job outlook for data scientists is very positive. The IBM predicts the demand for data scientist to soar 28% by 2020: https://www.forbes.com/sites/louiscolumbus/2017/05/13/ibm-predicts-demand-for-data-scientists-will-soar-28-by-2020/#7916f3057e3b

With so many professionals interested in data science, what is the best way to learn the fundamentals of data science?

Data Science is such a broad field that includes several subdivisions like data preparation and exploration; data representation and transformation; data visualization and presentation; predictive analytics; machine learning, etc. For beginners, learning the fundamentals of data science can be a very daunting task especially if you don’t have proper guidance as to the necessary training required, or what courses to take, and in what order?

I started learning about data science about a year ago. It was quite challenging…