CURRICULA Archives | Page 4 of 6

Forecasting and Trend Analysis

2021-03-12T03:57:54+00:00February 12th, 2019|Tags: Expert, Tech|

This course is an intuitive introduction to forecasting and analysis of time-series data. We will review a range of standard forecasting methods, including ARIMA and exponential smoothing, along with standard means of measuring forecast error and benchmarking with naive forecasts, and standard pre-processing/de-trending methods such as differencing and missing value imputation. Other topics will include trend/seasonality/noise decomposition, autocorrelation, visualisation of time series, and forecasting with uncertainty.

Advanced Python 1

2021-03-12T03:57:58+00:00March 5th, 2019|Tags: Tech, Expert|

This class builds on the introductory Python class. Jupyter Notebook advanced use and customisation is covered as well as configuring multiple environments and kernels. The Numpy package is introduced for working with arrays and matrices and a deeper coverage of Pandas data analysis and manipulation methods is provided including working with time series data. Data exploration and advanced visualisations are taught using the Plotly and Seaborne libraries.

Agile Insights

2021-04-13T04:26:47+00:00February 11th, 2019|Tags: Management, Non-tech, Expert, Business, C-suite|

This course presents a process and methods for an agile analytics delivery. Agile Insights reflects the capabilities required by any organisation to develop insights from data and validate potential business value. Content presented describes the process, how it is executed and how it can be deployed as a standard process inside an organisation. The course will also share best practices, highlight potential tripwires to watch out for, as well as roles and resources required.

Advanced R 1

2021-03-12T03:57:58+00:00March 1st, 2019|Tags: Expert, Tech|

This class builds on “Intro to R (+data visualisation)” by providing students with powerful, modern R tools including pipes, the tidyverse, and many other packages that make coding for data analysis easier, more intuitive and more readable. The course will also provide a deeper view of functional programming in R, which also allows cleaner and more powerful coding, as well as R Markdown, R Notebooks, and the shiny package for interactive documentation, browser-based dashboards and GUIs for R code.

Advanced R 2

2021-03-12T03:57:58+00:00March 1st, 2019|Tags: Tech, Expert|

This course goes deeper into the tidyverse family of packages, with a focus on advanced data handling, as well as advanced data structures such as list columns in tibbles, and their application to model management. Another key topic is advanced functional programming with the purrr package, and advanced use of the pipe operator. Optional topics may include dplyr on databases, and use of rmarkdown and Rstudio notebooks.

Overcoming Information Overload with Advanced Practices in Data Visualisation

2021-07-23T01:02:29+00:00May 14th, 2019|Tags: Management, C-suite, Business, Non-tech, Expert, Workshop, Stephen Brobst, Geospatial Analytics|

In this workshop, we explore best practices in deriving insight from vast amounts of data using visualisation techniques. Examples from traditional data as well as an in-depth look at the underlying technologies for visualisation in support of geospatial analytics will be undertaken. We will examine visualisation for both strategic and operational BI.

Agile Transition

2021-03-12T03:57:53+00:00February 11th, 2019|Tags: Non-tech|

This course describes the cultural and organisational aspects required for an organisation on the digital transformation path. A healthy corporate culture around data awareness is imperative to leverage the potential and value of data to the benefit of a company's business model. The organisation needs to reflect the culture and reward those who add value to a corporation by using data and analytics. Content presented explains personality and skill identification, how to prototype an agile analytics organisation and describe how to validate change capabilities, close gaps and execute a transition strategy.

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