Data Mining

What Will You Learn?

• Work with data using Python and pandas.
• Query and join data with SQL.
• Clean data and prepare it for analysis.
• Explore data and create clear charts.
• Apply clustering, classification, regression and association rules.
• Evaluate model results and explain the conclusions in business language.

Course Programme

1. Data Mining and Data Analytics

   The theoretical foundation of the course: key concepts and terms.

   Open Part 1

2. Python for Data Analysis

   Learn the basics of NumPy and pandas.

   Open Part 2

3. SQL for Data Analysts

   Filtering, joining, grouping and checking data.

   Open Part 3

4. Data Preparation and Data Quality

   Missing values, duplicate records, invalid values and outliers.

   Open Part 4

5. Exploratory Data Analysis and Visualisation

   Finding patterns and showing them with charts.

   Open Part 5

6. Statistics for Sector Analysis

   Comparing groups and testing hypotheses.

7. Clustering and Segmentation

   Clustering institutions by similar research profiles.

8. Classification, Regression and Association Rules

   Finding research areas that occur together (association rules).

9. Portfolio Project

   A complete project, from data preparation to writing recommendations.

Portfolio Project: Analytics of Scientific Research in Kazakhstan

You are an analyst of scientific activity in Kazakhstan. By analysing open research data on universities, research institutions and their researchers, you find out which institutions are developing and what research profiles exist.

The data you receive has had personal information removed.

Frequently Asked Questions

Who is the course for?

Anyone interested in data analysis. The course starts at the beginner level: no prior knowledge is required.

How does the course work?

You study at a time that suits you. There is a recommended schedule, but no mandatory deadlines.

Is the course free?

Yes, you can start the initial version for free.

Will I get a certificate?

Yes, we award a certificate after you complete the course.

What project will I work on?

You will analyse data on Kazakhstani universities, research institutions and researchers.

What kind of work does this course prepare me for?

Mainly the data analyst role. It also gives an introduction to Data Mining.

Which languages is the course available in?

The course is available in Kazakh and English. Some technical terms stay in English.

Who created the course?

The course was created by Ardan Zhanegiz.

The author earned a bachelor’s degree in Computer Science at Nazarbayev University and, through the Bolashak international programme, a master’s degree in Machine Learning and Big Data at the University of Wollongong in Australia, graduating with distinction.

The author is currently a doctoral student in Machine Learning and Data Science at Satbayev University.

The following sources were used in developing the course materials:

1. Kairanbay, M. (2023). Mashinany uiretu [Machine Learning]. In Kazakh.
2. Tan, P.-N., Steinbach, M., & Kumar, V. (2018). Introduction to Data Mining. Pearson/Addison-Wesley.
3. EMC Education Services (Ed.). (2015). Data Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data. John Wiley & Sons. https://doi.org/10.1002/9781119183686