Loading...

Data Culture Curriculum

An effective data analytics strategy in any organisation needs a program to build organisational culture around data; its ethical use, understanding, acceptance and its place in the daily conversation of what matters at all levels. Literacy around data, its purpose and management drives the development of that culture.

Data Literacy for Everyone

With the advent of automation, humans’ role has become to do what computers cannot. Many more white-collar workers—perhaps all of them—will end up “working with data” to some extent. This course for managers and workers without a strong quantitative background introduces a range of skills and applications related to critical thinking in such areas as forecasting, population measurement, set theory and logic, causal impact and attribution, scientific reasoning and the danger of cognitive biases. There are no prerequisites beyond high-school mathematics; this course has been designed to be approachable for everyone.

Fundamentals of AI, Machine Learning, Data Science and Predictive Analytics

Our leading course has transformed the artificial intelligence (AI), machine learning (ML) and data science practice of the many managers, sponsors, key stakeholders, entrepreneurs and beginning data analytics and data science practitioners who have attended it. This course is an intuitive, hands-on introduction to ai, data science and machine learning, it's your artificial intelligence 101. The training focuses on central concepts and key skills, leaving you with a deep understanding of the foundations of ai and data science and even some of the more advanced tools used in the field. The course does not involve coding, or require any coding knowledge or experience.

Best Practices in Enterprise Information Management

The effective management of enterprise information for analytics deployment requires best practices in the areas of people, processes, and technology. In this talk we will share both successful and unsuccessful practices in these areas. The scope of this workshop will involve five key areas of enterprise information management: (1) metadata management, (2) data quality management, (3) data security and privacy, (4) master data management, and (5) data integration.

Intro to R (+ data visualisation)

R is the world’s most popular data mining and statistics package. It’s also free, and easy to use, with a range of intuitive graphical interfaces. This two-day course will introduce you to the R programming language, teaching you to create functions and customise code so you can manipulate data and begin to use R self-sufficiently in your work.

Intro to Python for Data Analysis

Python is a high-level, general-purpose language used by a thriving community of millions. Data-science teams often use it in their production environments and analysis pipelines, and it’s the tool of choice for elite data-mining competition winners and deep-learning innovations. This course provides a foundation for using Python in exploratory data analysis and visualisation, and as a stepping stone to machine learning.

Overcoming Information Overload with Advanced Practices in Data Visualisation

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.

Data Ethics DRAFT

Data ethics is rapidly becoming the most critical aspect of engaging in a data driven, digital world. Significant backlash against industry giants like Facebook and Google for their data practices has pushed data ethics into mainstream society. With the ACCC signaling its intentions to focus on data practices and a host of new legislation, led by GDPR in Europe, the open data movement and the Consumer Data Right in Australia, it has become a key concern for digital consumers and the companies that serve them. The course covers the practical issues involved in implementing data ethics and uses real world illustrations and cases. We start with high profile data ethics cases and cover the essentials of the new legislation. We then walk through a data ethics policy. Day 2 focuses on a toolkit for implementing data trust and privacy by design, then covers consent and transparency requirements. It closes with a real-world framework for the governance required and an overview of the practical implementation steps.

Data Governance 1

This two day course provides an informed, realistic and comprehensive foundation for establishing best practice Data Governance in your organisation. Suitable for every level from CDO to executive to data steward, this highly practical course will equip you with the tools and strategies needed to successfully create and implement a Data Governance strategy and roadmap.

Agile Insights

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

Agile Transition

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.

Agile Data Management Architecture

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

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.