KNIME Analytics Platform is the leading open-source solution for data-driven innovation, helping you discover the potential hidden in your data, mine for fresh insights, or predict new futures. KNIME allows users to visually create data flows (or pipelines), selectively execute some or all analysis steps, and inspect the results and models with interactive views. With more than thousand modules, hundreds of ready-to-run examples, and the widest choice of advanced algorithms available, KNIME Analytics Platform is the perfect toolbox for any data scientist. Additional plugins allow the integration of methods for Text mining, Image mining, as well as time series analysis.

Programme objectives

• To introduce KNIME Analytics platform to the participants
• To introduce workflow-based approach for data analytics
• To apply machine learning techniques on data using KNIME
• To perform text analytics in KNIME

Who teaches the programme

The workshop will be led by Dr Sajid Siraj who is Lecturer in Business Analytics and Decision Science at Centre for Decision Research in Leeds University Business School. His research interests mainly lie in the areas of data analytics and decision making. He has used his skills in various areas including seismic data processing, telecom call detail records processing and profiling, and developing decision support systems.

To get most out of this workshop, you should:

• Know the use of Microsoft Excel (or any similar spreadsheet-based software).
• Know fundamentals of statistics (e.g. descriptive statistics and hypothesis testing).
• Have a Twitter account (if you’re interested in downloading tweets for text analytics).

The following will be beneficial, although not necessary:

• Computer programming and/or scripting skills.
• Basic knowledge of supervised and unsupervised machine learning

Costs

Students: £60
University staff, public and charitable sector staff: £100
Private Sector: £300

Provisional agenda

09:30    Introduction to the KNIME Workbench

10:00    Loading data from Excel

10:30    Table operations (column and row operations)

11:00   Break

11:30    Grouping data based on categorical variables

12:00    Visualizing data in bar and line plots etc.

12:30    Lunch 

13:30    Introduction to Text processing

14:30    Creating Twitter account and Getting API keys

15:00   Break

15:30    Capturing live tweets using Twitter API

16:30   Closing day 1