Course Objectives
Knowing how best express your results from your data science and machine learning algorithms is key to convincing your team and management your point of view. This programme will teach you visualisation techniques using Python as part of your data science workflow.
In this course, you will be shown how to leverage various Python libraries such as Matplotlib, Bokeh, Seaborn and others to enable you to focus on how to communicate with visualisations for maximum impact.
At the end of the programme, participants will be able to:
- Create and tell a story with Python visualisation with Python packages such as Matplotlib/Bokeh/Seaborn
- Build both static and interactive visualisation
- Understand good visual design principles
Outline
- Understanding Visualisation
- Pre-attentive Attribute
- Style
- Colour Theory
- Emphasis
- Do and Don’t
- Data Munging – a prelude to visualisation
- Understanding Notebook Environment
- Data Cleansing
- Data Filtering
- Tidy Data
- Advanced data structures and visualisation
- Slicing
- Aggregation
- Groupby
- Pivot
- Multi Index
- And How to Apply them in Visualisation
- Interactive graphics & Visualisation
- Matplotlib
- Seaborn
- Grammar of Graphics (ggplot)
- Bokeh
- Mini-Project: Creating various graphs
Tools
Jupyter, Python with the following packages: (Matplotlib, Seaborn, ggplot, Bokeh)
Pre-Requisites
Must be familiar with the Python programming language and statistics 101 at a pre-university level.
Who Should Attend
Software Engineers, Data Scientists, Data Analysts
Mode of Training
Classroom
Julian Lin
Dr
Julian Lin is a Senior Lecturer in Cybersecurity and Data Analytics with
School of Continuing and Lifelong Education (SCALE) at the National
University of Singapore (NUS). He is a Certified Information Systems
Security Professional (CISSP) and has a dozen other IT certifications.
Recently, Julian was ranked 6th in the Microsoft Data Science Capstone
Competition. He has been conducting text-analytics research since 2010
and teaching visualization since 2007. During his IT consultancy
career, he oversaw the application and infrastructure projects in
Amoseas, Mannesmann Dematic Colby (Sydney), Alcatel (Sydney), and the
University of New South Wales (UNSW) Faculty of Commerce and Economics.
Julian has taught programming and data management for business at UNSW.
At NUS, he had mentored student software development projects and
taught visual communications, designing new media content, and research
methods. He was given a teaching award for visualization class and
research award for user acceptance research in NUS. Julian obtained a
PhD degree in Information Systems from NUS. He was a recipient of two
scholarships from the Overseas Chinese Association in Taiwan while
pursuing his Bachelor degree and another scholarship while pursuing a
Master degree in Australia.