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Python training course; combining Python data science & analytics

15 January 2018

Python training course - a step in the right direction

There is currently a general agreement that Python is one the most versatile languages out there. People use Python for data analysis, and the words Python data science are often seen together.

So what exactly is data science anyway?

Data science as such has currently no exact definition, but the best description is that it is fundamentally a multidisciplinary subject comprising distinct though overlapping fields: 

  • Computer science and programming - for designing algorithms to store, process, and visualize this data; 
  • Statistics and probability - in order to model and summarize large data-sets; 
  • Relevant business expertise - so that insights can be used to drive business decisions to achieve business goals. 

As mentioned above, an exact definition of data science has yet to come. The fields above are agreed to constitute a necessary basis for a data scientist’s education. There are of course many other disciplines that are added and removed but those three are constant.
Data science is a very large field, and its goals include (among others): prediction, detection of patterns and anomalies, automating processes and decision-making, forecasting, etc.
It is important to note that there is a bit of confusion regarding the difference between data analysis and data science. So let us clarify:

Though data analysts share some of the data scientists’ skills and responsibilities concerning data, like accessing, querying, processing, summarising, visualising and reporting, (and have occasionally a similar educational background), there are some key differences however: 

  1. They are not programmers. Data analysts typically are not computer programmers, nor responsible for statistical modeling, machine learning,etc. 
  2. They use different tools. Data analysts often use tools for analysis and business intelligence, while data scientists perform these same tasks usually with tools such as Python.
  3. Data analysts hold different positions as regards top business managers and executives, i.e. data analysts are often given tasks from above to perform and then report their findings.
  4. Data scientists on the other hand, tend to generate the questions themselves, being familiar with the business goals and how the data can be used to achieve certain goals. 

So in order to become a data scientist, a profession which has been called “The Sexiest Job of the 21st Century” by the Harvard Business Review, it is only natural to enroll in a Python training course, whether you're a beginner or looking for an advanced python course. Thereafter, the road to integrate Python data science is clearly marked.

If you're interested in the world of Big Data, artificial intelligence an analysis, the variety of available courses and training is wide; you'd might consider data analytics courses, or other analytics courses; you'd might consider learning Python for machine learning or even R programming.
We offer on-location, multi-level training for you and your team; contact us today.


About the author: Craig Hartzel
Craig is a self-confessed geek who loves to play with and write about technology. Craig's especially interested in systems relating to e-commerce, automation, AI and Analytics.

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