Lifecycle of a Data Analytics Project

Participants experience a data analysis process from initial data gathering to generation of insights and visualisation of outputs. At each stage in the process participants will engage with real datasets and tools to facilitate the relevant tasks.

For this they will need to use a Python environment but – and we would like to stress this – in no way is this a Python programming course. Participants will make calls to pre-packaged Python code and, at most, tweak some parameters to get the desired output.

That said, source code will be available for review to those who may be interested in taking their Python journey independently of this programme.


This course is both for trainee data analysts and those working with DS teams. A grounding in Python fundamentals is helpful.

Learning Outcomes

Describe and implement a simple analytics project from start to finish from experience. This consists of:

  • data management
  • data visualisation
  • data preparation
  • data analysis and modelling
  • using data-driven insights to make meaningful business decisions.

Course Content

  • Formulating the problem statement: What are we trying to discover?
    • The use case will centre on stocks in an index.
    • Where data about those stocks (price, volatility, et al) is sufficient (or not)
    • Broad-brush statistical overview of the dataset.
    • Traditionally, stocks are clustered by sector – what if there are other, more useful ways of clustering them?
  • Data preparation: finding and eliminating null values (we will use a – predefined dataset with deliberate ‘errors’)
  • Data analysis: basic statistical outputs
    • percentiles, standard deviations, min/max/mean,
    • cluster analysis
  • Data Visualisation: Charting the cluster analysis
  • Data Storytelling: Interpreting the output and using it as the basis for meaningful business decision-making


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Why study with Alpha?

Innovation and creativity born from experience

We are thought leaders in instructional and learning journey design and holistic solution architects. We have extensive finance and investments experience combined with skills application to deliver performance improving results. We develop immersive learning environments that maximize time to productivity, support talent retention and added value to improving quality of hires.

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We are focused on mining the embedded organisational intellectual capital for the benefit of the next generation. We create and curate best in class practice gathered from our experience with the leading financial institutions. We design our programmes with the end in mind – what results are you trying to achieve with this intervention? What metrics will we set ourselves to achieve that?

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