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Išmanių ir klimatui neutralių kompetencijų centras Išmanių ir klimatui neutralių kompetencijų centro naujienos A series of lectures "Data Science for Business and Administration: Learning by doing“

2020-12-07

A series of lectures "Data Science for Business and Administration: Learning by doing“

We want to share the newest information regarding a series of lectures "Data Science for Business and Administration: Learning by Doing" was held for IT-masters from the Kyrgyz-German Institute of Applied Informatics, by the teacher of the Department of Business Technologies and Entrepreneurship Alexei Lurasov.

This course is practically oriented and divided into 12 different modules (based on business cases and datasets from different industries):

Churn Prediction: Telecommunications;
Customer Segmentation: Retail;
Market Basket Analysis: Grocery store;
Recommendation Engine: E-Commerce;
Credit Risk Assessment: Estimation of Probability of Default;
ClickStream Analysis: E-Commerce;
Demand prediction: Bike Sharing Company & Taxi Demand;
Cybersecurity: Fraud Detection in Credit Card Transactions;
Product Naming for Marketers and Retailers: Outdoor Clothing;
Social Media Analysis: Finding the Influencers and Sentiment Analysis;
Anomaly Detection for Internet of Things: Mechanic Failures Prediction;
Text Mining: Topic Detection for Corporate Forums and Blogs.

To practice Data Science on real business cases, Kirgisian IT master students decided to dive deeper into details of clickstream analysis for online shops. They examined the mass of data from:

the hundreds of thousands client web sessions extricated from the initial web log file;
the registered shopper’s database;
the product database, etc.

The tools for detection of visitor patterns and connections between their actions were developed. Applying data science to e-commerce clickstream data, the online shop can optimize their assortment and service, including targeted product suggestions, temporary advertisements, better web page layout and improved navigation options.
After completing the course students successfully passed KNIME certification to measure their expertise with different data science concepts and skills.

Student’s assessment of the course:

I am extremely grateful for the opportunity to take a course on Data Science. The course took place in an intensive mode and in a short time I was able to familiarize myself with a wide range of Data Science methods and algorithms. As a result, I managed to successfully pass the L1 certification “Basic Proficiency in KNIME Analytics Platform”. I would be glad to continue to participate in such master classes.

Mukanbetov Suiunduk