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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 [...]
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 science practitioners who have attended it. This course is an intuitive, hands-on introduction to data science and machine learning. The training focuses on central concepts and key skills, leaving the trainee with a deep understanding of the foundations of AI, 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.
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. This two-day course is an introduction to Python programming and Jupyter Notebooks, beginning with the most basic operations of downloading and installing the Python environment. The course will use Anaconda, a popular Python distribution for data science that includes many of the packages used in this course. The course will also introduce core Python objects and operations, Numpy for statistical and matrix operations, matplotlib and Plotly for visualisations, and Pandas, a comprehensive data manipulation and analysis package. Participants will learn how to input, read, write, and manipulate data, primarily using Pandas, and be instructed in all the aspects of procedural programming in Python, allowing them to create their own Python modules. Jupyter Notebooks will be featured as the recommended interface to write code, explore and analyse data, and to document and communicate the results of the data analysis with interactive visualisations. The course is focused on providing a foundation for participants to use Python for exploratory data analysis and visualisation, which can be used as a stepping stone to machine learning using the popular scikit-learn package and deep-learning packages unique to Python. Familiarity with Python will allow users to use packages and access data and web services that have existing connections to Python, e.g. natural language processing, APIs, and web scraping.
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. Through a mixture of tried and tested experiential and didactic learning techniques applied to the data science setting, participants develop the following skills relevant to innovative data scientists in the 21st century: creativity, a beginner’s mind, global citizenship, efficient communication, compassion, resilience, self-leadership, critical thinking, empathy, emergence/adaptability, self-awareness, & self-regulation. Equally, a deep appreciation for cultural, intellectual and gender diversity is gained.
As data becomes more and more critical both to the effective operation of organisations, and to their performance in an increasingly competitive landscape, the efficient and effective management of that data becomes crucial. Data governance refers to the processes and skills required to effectively manage data, whether big or small, traditional or digital. 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.
With big data expert and author Jeffrey Aven. 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 [...]