Data Project Fundamentals: Skills and Techniques for Success

This course aims to highlight the key skills that will make you stand out as a rounded Data Professional. You will cover the techniques, challenges and approaches undertaken in each of the logical stages of a data project. You will cover Data Profiling; Data Mapping and Transformation; Development; Data Modelling; Data Solution Design; Software Design; Unit Testing and Troubleshooting. The course aims to follow the natural life–cycle of a project.

These topics will be demonstrated by a mixture of lectures, screencasts, quizzes and exercises. Practical retail data will bring it all to life with Python and Jupyter Notebooks used to illustrate the techniques.  Although Jupyter notebooks are used, a running them in the course is that it is not important how certain techniques are done, but that these techniques are understood and why they form a key part of the process.  So although the hands–on sections will definitely enhance the course experience they are not a prerequisite, and could also be tackled using alternative software.

Ultimately this course aims to fill the gaps between courses focused on specific programming, data analysis skills or data modelling skills. It should allow you to appreciate but also critically question your current data environment.  I believe this course offers something different and will make you stand back and think before heading full–steam into a data–related task.  This more complete understanding of Data Projects will make you a better, more rounded Data Professional.  Enjoy!