Duration
14 hours (usually 2 days including breaks)
Requirements
- An understanding of Python programming.
- An understanding of Python libraries in general.
Audience
- Data analysts
- Data scientists
Overview
This instructor-led, live training (online or onsite) is aimed at data analysts and data scientists who wish to implement more advanced data analytics techniques for data mining using Python.
By the end of this training, participants will be able to:
- Understand important areas of data mining, including association rule mining, text sentiment analysis, automatic text summarization, and data anomaly detection.
- Compare and implement various strategies for solving real-world data mining problems.
- Understand and interpret the results.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Course Outline
Introduction
Overview of Data Mining Concepts
Data Mining Techniques
Finding Association Rules
Matching Entities
Analyzing Networks
Analyzing the Sentiment of Text
Recognizing Named Entities
Implementing Text Summarization
Generating Topic Models
Detecting Data Anomalies
Best Practices
Summary and Conclusion