For those who have a basic understanding of programming, to ensure that their data science projects always follow best practices in all, and to help emphasise the importance of best practices when working in a team – as we know, Data Science is a team sport. While all the Mango training courses help to instil these best practices; this course focuses on what the options are and why we need to use them in a language agnostic setting. This course outlines the key best practices associated with the 6 core traits of a data science team and project: communication, data wrangling, modelling, programming, technology, and visualisation.
Learn how to build packages with Python. Introduces the concept of writing efficient documentation, create tests and understand the benefits of version control systems with package building enhancement.
The basics of analytics, including sampling, statistical testing and linear modelling through Python. Provides the foundations for advanced analytic topics including machine learning.
Data Scientists and analysts are increasingly being asked to run or contribute to complex, multi-departmental projects with high expectations of success. Business and communication skills are rated as in top skills a data scientist needs to be successful. However, many individuals and teams struggle to develop them. The Trusted Consultant Programme helps data science and advanced analytics teams with a proven framework and tools they need to engage with stakeholders within their organisations in a positive, success-led manner. By the end of the course attendees will have developed the essential skills required to work with business stakeholders, work as part of a team to manage the project, and present analytic results to non-technical audiences.
For those already comfortable with programming in Python, this one day course is designed to provide an introduction to more advanced topics that will enable users to write more advanced Python code and give teams the tools they need to collaborate on larger Python code-bases. Including introductions to object oriented systems and more advanced function control, by the end of this course attendees will be able to make their code easier for end users to interact with, faster and more robust.
When it comes to forecasting time dependent data we need to consider a range of techniques beyond those common in machine learning to get the most from our data. In this one-day course attendees will be introduced to some of the common time series analysis techniques as well as how to implement and understand them in Python. In addition we will cover some of the common manipulation tasks related to dates and times and how we can create visualisations to aid our analysis.
This two day course is aimed at not only teaching an understanding of some of the most common machine learning techniques, but also the approach to implementing machine learning. During this course attendees will learn how to define a problem and prepare data, the range of techniques available for solving common problems and the approaches to take to evaluate models and achieve the best results possible.
Once you have started to use Python for common data manipulation tasks you will quickly find that you want to be able to do more. This one day course introduces the topics that you will need to be familiar with in order to get the most from Python. This course will go into detail on essential Python knowledge including how to manage your installation of Python, the main Python data structures and how to iterate over them in a Pythonic way. This course will also teach you how to write functions and use them in the context of data analysis to write data pipelines.
This two day introduction to Python focuses on getting started with common data tasks. By the end of this course, attendees will be confident in how they can import data, perform common manipulation tasks and visualise data. Along the way they will be introduced to a variety of data types including dates and categorical data.
Focused around a specific business problem, this one day workshop will work through the data analysis workflow to give attendees an understanding of how a data scientist would approach and look to answer an analytic question. The day will work through modelling approaches that are relevant to the question in hand, introduce best practices around modelling and data analysis and leave attendees with the ability to put into practice what they have seen.