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).

The Future of Analytics

2021-07-23T01:04:45+00:00May 18th, 2019|Tags: , , , , , , |

This full day workshop examines the trends in analytics deployment and developments in advanced technology. The implications of these technology developments for data foundation implementations will be discussed with examples in future architecture and deployment. This workshop presents best practices for deployment of a next generation data management implementation as the realization of analytic capability for mobile devices and consumer intelligence. We will also explore emerging trends related to big data analytics using content from Web 3.0 applications and other non-traditional data sources such as sensors and rich media.

Advanced Deep Learning

2021-07-26T01:19:34+00:00December 5th, 2018|Tags: , |

This course provides a more rigorous, mathematically based view of modern neural networks, their training, applications, strengths and weaknesses, focusing on key architectures such as convolutional nets for image processing and recurrent nets for text and time series. This course will also include use of dedicated hardware such as GPUs and multiple computing nodes on the cloud. There will also be an overview of the most common available platforms for neural computation. Some topics touched in the introduction will be revisited in more thorough detail. Optional advanced topics may include Generative Adversarial Networks, Reinforcement Learning, Transfer Learning and probabilistic neural networks.

Advanced Fraud and Anomaly Detection

2021-04-13T04:01:44+00:00February 12th, 2019|Tags: , |

The detection of anomalies is one of the most eclectic and difficult activities in data analysis. This course builds on the basics introduced in the earlier course, and provides more advanced methods including supervised and unsupervised learning, advanced use of Benford’s Law, and more on statistical anomaly detection. Optional topics may include anomalies in time series, deception in text and the use of social network analysis to detect fraud and other undesirable behaviours.

Innovating with Best Practices to Modernise Delivery Architecture and Governance

2021-07-23T01:01:04+00:00May 20th, 2019|Tags: , , , , , |

Organisations often struggle with the conflicting goals of both delivering production reporting with high reliability while at the same time creating new value propositions from their data assets. Gartner has observed that organizations that focus only on mode one (predictable) deployment of analytics in the construction of reliable, stable, and high-performance capabilities will very often lag the marketplace in delivering competitive insights because the domain is moving too fast for traditional SDLC methodologies. Explorative analytics requires a very different model for identifying analytic opportunities, managing teams, and deploying into production. Rapid progress in the areas of machine learning and artificial intelligence exacerbates the need for bi-modal deployment of analytics. In this workshop we will describe best practices in both architecture and governance necessary to modernise an enterprise to enable participation in the digital economy.

Modernising Your Data Warehouse and Analytic Ecosystem

2021-07-23T01:01:37+00:00May 20th, 2019|Tags: , , , , |

This full-day workshop examines the emergence of new trends in data warehouse implementation and the deployment of analytic ecosystems.  We will discuss new platform technologies such as columnar databases, in-memory computing, and cloud-based infrastructure deployment.  We will also examine the concept of a “logical” data warehouse – including and ecosystem of both commercial and open source technologies.  Real-time analytics and in-database analytics will also be covered.  The implications of these developments for deployment of analytic capabilities will be discussed with examples in future architecture and implementation. This workshop also presents best practices for deployment of next generation analytics using AI and machine learning. 

Cost-Based Optimisation: Obtaining the Best Execution Plan for Complex Queries

2021-07-23T01:00:08+00:00May 20th, 2019|Tags: , , , |

Optimiser choices in determining the execution plan for complex queries is a dominant factor in the performance delivery for a data foundation environment. The goal of this workshop is to de-mystify the inner workings of cost-based optimisation for complex query workloads. We will discuss the differences between rule-based optimisation and cost-based optimisation with a focus on how a cost-based optimization enumerates and selects among possible execution plans for a complex query. The influences of parallelism and hardware configuration on plan selection will be discussed along with the importance of data demographics. Advanced statistics collection is discussed as the foundational input for decision-making within the cost-based optimiser. Performance characteristics and optimiser selection among different join and indexing opportunities will also be discussed with examples. The inner workings of the query re-write engine will be described along with the performance implications of various re-write strategies.

Optimising Your Big Data Ecosystem

2021-07-23T01:02:03+00:00May 18th, 2019|Tags: , , , , |

Big Data exploitation has the potential to revolutionise the analytic value proposition for organisations that are able to successfully harness these capabilities. However, the architectural components necessary for success in Big Data analytics are different than those used in traditional data warehousing. This workshop will provide a framework for Big Data exploitation along with recommendations for architectural deployment of Big Data solutions.

Agile Data Management Architecture

2021-07-23T00:57:04+00:00May 18th, 2019|Tags: , , , |

This full-day workshop examines the trends in analytic technologies, methodologies, and use cases. The implications of these developments for deployment of analytic capabilities will be discussed with examples in future architecture and implementation. This workshop also presents best practices for deployment of next generation analytics.

Social Network Analysis: Practical Use Cases and Implementation

2021-07-23T01:03:21+00:00May 13th, 2019|Tags: , , , |

Social networking via Web 2.0 applications such as LinkedIn and Facebook has created huge interest in understanding the connections between individuals to predict patterns of churn, influencers related to early adoption of new products and services, successful pricing strategies for certain kinds of services, and customer segmentation. We will explain how to use these advanced analytic techniques with mini case studies across a wide range of industries including telecommunications, financial services, health care, retailing, and government agencies. 

Capacity Planning for Enterprise Data Deployment

2021-07-23T00:59:25+00:00December 6th, 2018|Tags: , , , |

This workshop describes a framework for capacity planning in an enterprise data environment. We will propose a model for defining service level agreements (SLAs) and then using these SLAs to drive the capacity planning and configuration for enterprise data solutions. Guidelines will be provided for capacity planning in a mixed workload environment involving both strategic and tactical decision support. Performance implications related to technology trends in multi-core CPU deployment, large memory deployment, and high density disk drives will be described. In addition, the capacity planning implications for different approaches for data acquisition will be considered.

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