Python for Analysis and Automation

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June 8, 19:00
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This course is a bridge between chaotic spreadsheets and intelligent automation. We do not simply teach Python syntax — we build tools that work for you: from automatically pulling data out of BigQuery to dispatching finished reports.

Who Is This Course For?

  • Data Analysts: Who want to move beyond Excel and Power BI by mastering the flexibility of code.
  • Marketers and Growth Hackers: Who need to automate reporting and segment customers.
  • Managers: Who want to understand the technical side of products and work with Big Data independently.
  • SQL Users: Who wish to deepen their analysis using Pandas and Machine Learning libraries

Why Choose This Course?

  • Streamlined Curriculum: We removed the unnecessary and merged data visualisation with data processing for a seamless workflow.
  • Deep Technical Foundation: Added blocks on algorithms and data structures — turning you into a real developer, not just a ‘library user’.
  • Autonomy: You will learn how to run scripts on a server (scheduler) so they keep working while you rest.

Course Curriculum

MODULE 1
Python Fundamentals and Computer Science

Lesson 1. Introduction to Python + Working with Strings
Lesson 2. Data Collections (lists, tuples, sets, dictionaries)
Lesson 3. Conditions and Loops
Lesson 4. Functions and Modules
Lesson 5. Working with Files + Error Handling
Lesson 6. Python Infrastructure: decorators, iterators, generators
Lesson 7. Basics of Classes and OOP in Python

MODULE 2
Data Processing: Pandas, NumPy, Databases, SQL, BigQuery, and Automation

Lesson 8. Introduction to Pandas and NumPy
Lesson 9. Data Operations in Pandas
Lesson 10. Grouping, Aggregation, and Merging in Pandas. Data Visualisation: matplotlib + plotly
Lesson 11. Databases and SQL in Python
Lesson 12. Specialised Data Structures
Lesson 13. Algorithmic Approaches in the Context of Data Processing
Lesson 14. Report Generation (Excel, HTML, PDF)
Lesson 15. Automated Report Distribution
Lesson 16. Automatic Script Scheduling (scheduler)

MODULE 3
ML, Segmentation, and Forecasting

Lesson 17. Customer Segmentation and In-Depth Behaviour Analysis
Lesson 18. Forecasting and Integration of Predictive Models into Business Processes

Learning Outcomes

  1. Design ETL Processes: You will learn to automatically extract data from databases and BigQuery, transform it, and store the results.
  2. Master Complex Structures: You will fluently apply algorithms and data structures to write efficient, optimised code.
  3. Build a Digital Office: You will configure automated report generation (PDF/Excel) and scheduled distribution.
  4. Deploy ML Models: You will forecast key metrics and segment customers using machine learning algorithms.
  5. Automate Routine Work: You will free up to 70% of the time previously spent on repetitive report preparation

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