Data Engineering Curriculum

The Data Engineering Curriculum is for IT professionals, data engineers, data analysts, and those supporting data science. The levels build up on another, each block represents a class of two days.

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

2020-11-02T23:25:54+00:00Categories: Predictive Analytics & AI, Level 1, Data Science Curriculum, Data Governance Curriculum, Executive Curriculum, Data Engineering Curriculum, Dr Eugene Dubossarsky, Innovation and Technology Curriculum, AI Engineering Curriculum, All Academy Courses|Tags: , , , , |

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 fundamentals and key skills, leaving you with a deep understanding of the core concepts 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. As our leading course, it 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.

Data-Driven Management

2020-09-17T07:24:02+00:00Categories: AI Engineering Curriculum Electives, Data Engineering Curriculum Electives, Government, Data Science Curriculum, Data Governance Curriculum, Executive Curriculum, Dr Eugene Dubossarsky, Innovation and Technology Curriculum, All Academy Courses|Tags: , , , |

The Data-Driven Management course is for executives and managers who want to leverage analytics to support their most vital decisions and enable better decision-making at the highest levels. It empowers senior executives with skills to make more effective use of data analytics. It covers contexts including strategic decision-making and shows attendees ways to use data to make better decisions. Attendees will learn how to receive, understand and make decisions from a range of analytics methods, including visualisation and dashboards. They will also be taught to work with analysts as effective customers.

Report Automation – Excel to PowerPoint with R

2020-10-30T03:38:27+00:00Categories: Dr Craig Savage, Data Engineering Curriculum Electives, Data Science Curriculum Electives, R, Data Visualisation, All Academy Courses|Tags: , , , |

Report automation can deliver powerful, time-saving results. This course teaches analytics professionals to automate the creation of PowerPoint packs from input Excel workbooks using R. Time is allotted for students to implement techniques taught so that, by the end of the course, students will have wrangled input data, created plots and tables, defined a PowerPoint template, and built a sample set of slides.

Data Governance I

2020-09-18T02:53:29+00:00Categories: Data Culture Electives, Government, Data Science Curriculum, Data Governance Curriculum, Executive Curriculum, Mark Burnard, Data Engineering Curriculum, Innovation and Technology Curriculum, AI Engineering Curriculum, Financial Risk, All Academy Courses|Tags: , , , |

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.

Intro to R (+ data visualisation)

2020-10-19T01:35:22+00:00Categories: Level 1, Data Culture Electives, Impact, Data Science Curriculum, R, Data Visualisation, Data Engineering Curriculum, Dr Eugene Dubossarsky, AI Engineering Curriculum, All Academy Courses|Tags: , |

This R training 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. 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.

Intro to Python for Data Analysis

2020-11-03T00:09:02+00:00Categories: Level 1, Data Culture Electives, Data Science Curriculum, Python, Data Engineering Curriculum, Dr Eugene Dubossarsky, AI Engineering Curriculum, All Academy Courses|Tags: , |

This course provides a foundation for using Python in exploratory data analysis and visualisation, and as a stepping stone to machine learning. 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.

Data Science and Big Data Analytics: Leveraging Best Practices and Avoiding Pitfalls

2020-10-26T10:07:42+00:00Categories: Data Engineering Curriculum Electives, Data Science Curriculum, Data Governance Curriculum Electives, Stephen Brobst, Executive Curriculum, Data Visualisation, Data Management, Big Data, All Academy Courses|Tags: , , , , , , |

Data science is the key to business success in the information economy. This workshop will teach you about best practices in deploying a data science capability for your organisation. Technology is the easy part; the hard part is creating the right organisational and delivery framework in which data science can be successful in your organisation. We will discuss the necessary skill sets for a successful data scientist and the environment that will allow them to thrive. We will draw a strong distinction between “Data R&D” and “Data Product” capabilities within an enterprise and speak to the different skill sets, governance, and technologies needed across these areas. We will also explore the use of open data sets and open source software tools to enable best results from data science in large organisations. Advanced data visualisation will be described as a critical component of a big data analytics deployment strategy. We will also talk about the many pitfalls and how to avoid them.

Data Governance II

2020-12-02T02:02:44+00:00Categories: Executive Curriculum Adv Electives, Data Culture Electives, Government, Data Science Curriculum, Data Governance Curriculum, Mark Burnard, Data Engineering Curriculum, Innovation and Technology Curriculum, AI Engineering Curriculum, Financial Risk, All Academy Courses|Tags: , , , |

This one day course builds on the foundation of Data Governance I, and dives deeper into selected areas that are designed to provide the most practical and real-world applications of data governance. It includes the change management journey to the “data-driven” organisation, and implications of the necessity of model governance in the context of data science, AI/ML initiatives and RPA/IPA .

Leadership and Resilience Skills for Data Professionals

2020-09-18T03:04:04+00:00Categories: Data Science Curriculum, Leadership & Management, Data Engineering Curriculum, Katrina Loukas, All Academy Courses|Tags: , |

Many people today have been developed emotionally and mentally for an era that no longer really exists. This has created a critical soft-skills gap between current workforce ability and business requirements today. In this course participants learn to ‘readapt’ their soft skills so that they are aligned with a thriving 21st century business. They are also given a simple framework from which to continue the self-development so that the training instigates sustainable change.

Data Transformation and Analysis Using Apache Spark

2020-10-19T06:52:15+00:00Categories: Jeffrey Aven, Level 1, Apache Spark Training with Jeffrey Aven, Experienced Analytics Instructor + Big Data Author, Data Science Curriculum Electives, Data Governance Curriculum Electives, Apache Spark, Data Engineering Curriculum, All Academy Courses|Tags: , |

With big data expert and author Jeffrey Aven. Learn how to develop applications using Apache Spark. The first module in the “Big Data Development Using Apache Spark” series, this course provides a detailed overview of the spark runtime and application architecture, processing patterns, functional programming using Python, fundamental API concepts, basic programming skills and deep dives into additional constructs including broadcast variables, accumulators, and storage and lineage options. Attendees will learn to understand the Apache Spark framework and runtime architecture, fundamentals of programming for Spark, gain mastery of basic transformations, actions, and operations, and be prepared for advanced topics in Spark including streaming and machine learning.

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