Business decisions often require presentation of data and metrics in a graphical manner to intuitively understand underlying realities. This is achieved through Analytics, the science of data discovery and interpretation. Graphical Visualization is an an offshoot of Analytics that helps interpret the underlying statistically and visually for its interpretation.  

The course on Data Analytics and Visualization would help analysts, consultants, and business leaders to familiarize themselves with state-of-art techniques of data analysis and visualization. This fully hands-on course uses Python, the official language adopted by Google, and its relevant libraries. Participants would use Spyder IDE to complete 50+ structured assignments generating over 2.5K lines of Python code, during the course.

Coverage: Language elements, data types, frames, plots, using pandas, numpy, and matplotlib libraries. Algorithms, functions, colors, color maps, and plotting functions. Graphical techniques such as line, bar, scatter, polar, histograms, density, and multi-plots. Exemplary short projects. 

Duration: 10 hours (webx / contact), equal offline hours on assignments (participants to use their laptops/desktops).