The seminar can be held online on the official International Business Academy platform. On completion of the training you will be given a link to the recording, which will be available for one month.
*dates are subject to additional confirmation
excluding VAT
* VAT of 16% will be added to the invoice
The course «Python for business analysts» is intended for specialists working with data, reporting and analytics who want to automate routine processes, increase the speed of processing information and use modern analytics and artificial intelligence tools in their work.
The course programme combines practical study of Python with business analysis tools, data processing and building intelligent reporting. Participants will learn to work with databases, process large volumes of information, create automated analytical reports and visualise the business's key indicators.
Special attention is paid to applying artificial intelligence and modern AI tools for forecasting, identifying patterns and automatically interpreting data. During the training, participants will master methods of predictive analytics, customer segmentation, text data analysis and building sales and business indicator forecasting models.
The course is built to be as practical as possible and is oriented towards real business tasks. Participants will work with DataFrames, SQL queries, Excel and PDF reports, as well as data visualisation and AI analytics tools.
During the course, participants will learn to:
• use Python to process and analyse data;
• work with PostgreSQL and ClickHouse;
• apply Pandas to prepare analytical samples;
• automate the generation of Excel, Word and PDF reports;
• build visualisations and analytical dashboards;
• use AI to forecast indicators and analyse trends;
• perform automatic customer segmentation;
• analyse text reviews with NLP;
• form intelligent analytical reports with automatic conclusions.
The practical outcome of the course will be the development of a full-fledged analytical solution with elements of forecasting, visualisation and automatic interpretation of data, which can be applied in a company's real work.
Python basics for business analytics and working with data
• Introduction to Python for analysts
• Preparing the development environment and connecting libraries
• Python syntax basics for data processing
• Working with variables, lists, dictionaries and functions
• Reading and processing data from Excel and CSV files
• Using the Pandas and NumPy libraries
• Creating and working with DataFrames
• Filtering, sorting and aggregating data
• Practice: processing business data and preparing analytical tables
SQL and working with databases
• SQL basics for analytics
• Connecting Python to PostgreSQL and ClickHouse
• Running SQL queries from Python
• Retrieving data from corporate databases
• JOIN, GROUP BY, filtering and aggregating data
• Combining data from different sources
• Preparing analytical samples
• Automating data loading for reporting
• Practice: creating analytical queries for business tasks
Data visualisation and automating reporting
• Building graphs and charts with Matplotlib
• Visualising sales dynamics, KPIs and business indicators
• Setting up analytical charts and reports
• Automatically generating Excel reports
• Generating Word and PDF documents
• Preparing regular management reporting
• Automating the export of analytical data
• Practice: creating an analytical dashboard and an automatic report
Artificial intelligence and forecasting in analytics
• Introduction to AI for business analytics
• Using AI tools to process data
• Building models to forecast indicators
• Analysing sales trends and forecasting dynamics
• Automatic customer segmentation
• NLP basics for analysing text reviews
• Using AI to automatically generate analytical conclusions
• Practice: building an intelligent analytical model
Developing an intelligent analytical solution
• Building a unified analytical process
• Integrating Python, SQL and AI tools
• Automating the full analytics cycle
• Forming forecast reports and visualisations
• Preparing analytical conclusions for the business
• Developing the final analytical project
• Practice: creating an intelligent report with forecasting
• Presentation and review of participants' finished solutions
