AI Engineering Curriculum

Training Courses, Workshops and Seminars

A curriculum for those specialising in the automatic scaling and deployment of enterprise machine learning and artificial intelligence (AI).

Advanced Python 1

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

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: , , , , |

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: , |

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: , |

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: , , , , , , , |

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.

Advanced Python 2

2021-04-13T04:06:24+00:00March 5th, 2019|Tags: , |

In the Advanced Python 2 course, you will learn advanced methods and packages for working with "big data" with Pandas. The course also covers using Dask for parallel computation. Machine learning is demonstrated with [...]

Advanced Machine Learning Masterclass I

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

This course is for experienced machine-learning practitioners who want to take their skills to the next level by using R to hone their abilities as predictive modellers. Trainees will learn essential techniques for real machine-learning model development, helping them to build more accurate models. In the masterclass, participants will work to deploy, test, and improve their models.

Understand Blockchain, Smart Contracts and Cryptocurrency

2021-07-16T05:05:48+00:00February 21st, 2019|Tags: , , , |

Blockchain is one of the most disruptive and least understood technologies to emerge over the previous decade. This course gives participants an intuitive understanding of blockchain in both public and private contexts, allowing them to distinguish genuine use cases from hype. We explore public crypto-currencies, smart contracts and consortium chains, interspersing theory with case studies from areas such as financial markets, health care, trade finance, and supply chain. The course does not require a technical background.

Quantum Computing

2021-03-12T03:57:56+00:00February 22nd, 2019|Tags: , , , |

This course is an introduction to the exciting new field of quantum computing, including programming actual quantum computers in the cloud. Quantum computing promises to revolutionise cryptography, machine learning, cyber security, weather forecasting and a host of other mathematical and high-performance computing fields. A practical component will include writing quantum programs and executing them on simulators as well as on actual quantum computers in the cloud.

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