One Day Seminar on “Jump Start on Data Mining” By Dr. Chen Nan
26 January 2018, Friday
9am – 5pm
Venue: National University of Singapore
The proposed course encompasses introductory data mining and practical approaches to machining learning tools and techniques ranging from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods. The course is structured around a few real examples to discuss the techniques of major data mining approaches. Well-designed hands-on exercises will be walked through to facilitate their applications in practice.
The course is an insightful introduction to data mining methods and practice. It gives a jump start to interested trainees to use data mining techniques in their daily work. In addition to algorithmic methods and hands on programming exercises, the course will also focus approaches to tackle real problems and interpret the results to discover meaningful insights as demonstration of the power of big data analytics.
At the end of the course, participants should be able to
- Understand and recognize different data mining problems in practice
- Understand and use classical data mining methods in regression, classification, and clustering
- Perform real data analysis, and evaluate, compare, and diagnose the performance in applying the methods in practice
Who Should Attend
The target audience include fresh graduates and junior employees who have strong interests in data mining techniques, and want to use them in their day to day work. Prior experience in data mining is not required, but some programming experience can be helpful in learning the tools in data mining.
- Introduction to different data mining problems
- Model evaluation
- Regression Techniques
- Decision tree, random forest
- Neural network,
- Classification Techniques
- Logistic regression
- Case study and hands on tutorial
- Introduction to Python
- Tools and packages for machine learning
· Free Admission for first 10 TDSI Alumni
· SGD856.00 per pax (including GST) for Non MDTS Alumni
CHEN Nan is an Associate Professor in the Department of Industrial Systems Engineering and Management (ISEM) at the National University of Singapore (NUS). He graduated from Tsinghua University with BS degree in Automatic Control. Subsequently, he obtained his PhD degree in Industrial Engineering, MS degree in Computer Science, MS degree in Statistics, all from University of Wisconsin Madison. His research focused on data analytics approaches in improving quality and reliability in complex engineering systems. He has extensive experience in different data mining techniques in real applications from his past research and projects.
Enquiry and Registration
Please contact Ms Queenie Sim at firstname.lastname@example.org or +65 6516 5838 for more information.