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overview
Key Learning Objectives
- Understand key concepts and trends in text mining analytics
- Understand use cases of text mining analytics
- Create scalable, interactive and actionable text mining analytics capabilities
- Collect, input and visualise text data from surveys, social media and documents
- Effectively organise your text for effective data visualisation
- Data science and analytics strategy fundamentals
- Creating text analytics solutions using data science and predictive analytics
About the Course
Data is now a ubiquitous asset in any and all organisations. But the reality is that the vast majority of data generated is of an unstructured format. This poses interesting challenges to those who need to make sense of it. One of the most prevalent types of unstructured data in the world is in the form of written text. Think about it: All the documents that get created in your organisation, all the emails that get sent around and all the conversation that happens in social media and other online settings.
In this two-day introductory yet highly-practical workshop, participants will learn the latest theories, tools, techniques and strategies for applying advanced analytics in situations where data exists in the form of texts and written documents. Aimed at beginners, this workshop will help professionals with fundamental ideas and practical knowledge to positively impact their organisations.
Who Will Benefit
- For those who want to understand how analytics is being applied in the context of text and documents but have not had any (or major) exposure to the field.
- For those who want to pursue a change in careers to work more closely with data, analytics and data science with emphasis on text from surveys, documents and social media but have not had a chance to figure out how.
- For those who work for organisations that must deal with a lot of text in the form of documents, surveys, texts and social media and want to apply analytics to it but have not had a chance to figure out how to start.
Pre-Requisites
None. Participants need only to come interested to learn, interact with each other and to dedicate themselves to learning and participating during sessions.
Testimonials
Really enjoyable course in an exciting and growing subject. Felipe was an enthusiastic, encouraging and engaging presenter!
– Business Intelligence Lead, Forensicare
Felipe was very knowledgeable in skills, theory, best practices and current information on data visualisation. Very engaged and supportive in listening to our ideas and input with great discussions and teaching.
– Creative Designer, UNSW Sydney
Course Outline
DAY ONE
Fundamental concepts in analytics, data science and machine learning
- Historical overview, recent developments and future outlook of advanced analytics topics
- Demystifying some key definitions, concepts and terminologies in data
- Knowing your why, and what your data analytics capability needs to achieve
Implementing a data science and analytics capability in your organisation
- Making sense of your organisation’s data science and analytics capability and maturity
- Plotting a roadmap from business strategy to data science realisation
- Understanding what makes organisations do data science and machine learning right
Beginning with basic applied statistics in a business settings
- Explore and work through a practical application of exploratory data analysis (EDA)
- Introduce and apply a basic machine learning model to a simple dataset in real life
- Utilise a popular business tool to interpret and summarise the results of a predictive model
Data, technology and privacy examples for successful analytics in your organisation
- Overview and examples of data, technology platforms, privacy and ethics in analytics
- How to manage data and technology effectively and the importance of tool selection and usage
- Discuss a variety of tools in both open source + commercial spaces and their pros and cons
DAY TWO
What is the difference with text mining analytics?
- Understand fundamental concepts and nuances of data science behind text mining analytics
- Explore the latest ideas with case studies in data science powering robust text mining solutions
- Working with predictive analytics models and basic algorithms in text mining analytics
Practical Case Study: Analysing sentiment in social media contexts
- Understand key concepts behind delivering a sentiment analysis project
- Explore and work through a practical example of sentiment analysis on social media posts
- Discuss and showcase implications and applications of sentiment analysis
Practical Case Study: Predicting and classifying NPS survey results and comments
- Understand basic concepts and steps in building a text prediction and classification solution
- Explore and work through a practical example of a NPS survey to build a classifier
- Discuss and showcase implications and applications of predicting and classifying comments
Text mining analytics in action
- Revisit main themes, tools, techniques and strategies
- Build a practical action plan to apply text mining analytics to your organisation
- Group discussion, final reflections and insights
when & where
16 - 17 Mar 2020
Sydney
On-site & in-house training
Deliver this course how you want, where you want, when you want – and save up to 40%! 8+ employees seeking training on the same topic?
Talk to us about an on-site/in-house & customised solution.
contact
Still have a question?
Sushil Kunwar
Training Consultant
+61 (0)2 9080 4395
training@informa.com.au