Algorithmic Trading with Python and R Training Course

This instructor-led, live training in Poland (online or onsite) is aimed at intermediate-level participants who wish to master advanced data integration and visualization techniques in Looker Studio, and learn how to connect diverse data sources, design compelling dashboards, and automate reporting workflows to drive better business decisions.

By the end of this training, participants will be able to:

• Connect and integrate multiple data sources into Looker Studio.
• Create custom metrics and calculated fields for tailored analysis.
• Design advanced visualizations, including interactive filters and charts.
• Automate reporting workflows for real-time data updates.
• Apply best practices for visual storytelling and report customization.

This instructor-led, live training in Poland (online or onsite) is aimed at data scientists and software engineers who wish to use Dask with the Python ecosystem to build, scale, and analyze large datasets.

By the end of this training, participants will be able to:

• Set up the environment to start building big data processing with Dask and Python.
• Explore the features, libraries, tools, and APIs available in Dask.
• Understand how Dask accelerates parallel computing in Python.
• Learn how to scale the Python ecosystem (Numpy, SciPy, and Pandas) using Dask.
• Optimize the Dask environment to maintain high performance in handling large datasets.

This instructor-led, live training in Poland (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy.

By the end of this training, participants will be able to:

• Set up a development environment that includes Python, Pandas, and NumPy.
• Create a data analysis application using Pandas and NumPy.
• Perform advanced data wrangling, sorting, and filtering operations.
• Conduct aggregate operations and analyze time series data.
• Visualize data using Matplotlib and other visualization libraries.
• Debug and optimize their data analysis code.

This instructor-led, live training in Poland (online or onsite) is aimed at intermediate-level data professionals who wish to implement a lakehouse solution using Microsoft Fabric.

By the end of this training, participants will be able to:

• Understand the architecture and components of Microsoft Fabric.
• Configure and manage a Lakehouse using Microsoft Fabric.
• Ingest and transform data using Apache Spark.
• Utilize Delta Lake tables for versioning and managing data.
• Implement data ingestion pipelines with Dataflows Gen2.
• Orchestrate data pipelines using Data Factory.

This instructor-led, live training in Poland (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to enhance their productivity and efficiency by leveraging the advanced features of Excel and Google Sheets for data organization, analysis, and collaboration.

By the end of this training, participants will be able to:

• Navigate and utilize the core features of Excel and Google Sheets.
• Perform data analysis and create actionable insights using advanced spreadsheet techniques.
• Collaborate in real-time using Google Sheets for seamless teamwork.
• Create reusable templates for reporting, tracking, and project management.

This instructor-led, live training in (online or onsite) is aimed at developers who wish to use the FARM (FastAPI, React, and MongoDB) stack to build dynamic, high-performance, and scalable web applications.

By the end of this training, participants will be able to:

• Set up the necessary development environment that integrates FastAPI, React, and MongoDB.
• Understand the key concepts, features, and benefits of the FARM stack.
• Learn how to build REST APIs with FastAPI.
• Learn how to design interactive applications with React.
• Develop, test, and deploy applications (front end and back end) using the FARM stack.

This instructor-led, live training in Poland (online or onsite) is aimed at developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs easier and faster.

By the end of this training, participants will be able to:

• Set up the necessary development environment to develop APIs with Python and FastAPI.
• Create APIs quicker and easier using the FastAPI library.
• Learn how to create data models and schemas based on Pydantic and OpenAPI.
• Connect APIs to a database using SQLAlchemy.
• Implement security and authentication in APIs using the FastAPI tools.
• Build container images and deploy web APIs to a cloud server.

The training focuses on practical learning of creating REST APIs using the FastAPI framework. Participants will learn the complete process of building a web application—from understanding client-server architecture and the HTTP protocol, through implementing all CRUD operations, to integrating with a database and securing the application.

The program includes working on a simple, example project that participants build step by step. They will learn to define endpoints, validate input data using Pydantic, handle errors, and return appropriate HTTP status codes. They will also explore two approaches to working with databases: direct SQL queries through psycopg and ORM SQLAlchemy.

We place a strong emphasis on code organization—modularization, separation of logic, and good practices for project structuring. Participants will also learn to test their APIs using TestClient, work with automatically generated documentation, and implement authentication and password hashing mechanisms.

After the training, participants will be able to independently design and implement functional REST APIs connected to a database, secured, and ready for further development. They will gain practical knowledge that allows them to start working as backend developers in Python.

This instructor-led, live training in Poland (online or onsite) is aimed at data analysts who wish to use Google Sheets for data analysis.

By the end of this training, participants will be able to:

• Build spreadsheets with Google Sheets.
• Use formulas that work both in Google Sheets and Excel.
• Format and analyze any data.
• Create data visualizations with charts and graphs.

This instructor-led, live training in Poland (online or onsite) is aimed at beginner-level to intermediate-level participants who wish to build foundational skills for data visualization and reporting using Looker Studio, and learn how to connect data sources, visualize information effectively, and gain actionable insights.

By the end of this training, participants will be able to:

• Understand the core features of Looker Studio and its use cases.
• Set up Looker Studio and connect to various data sources.
• Create engaging dashboards with charts, graphs, and filters.
• Customize reports for specific audiences and business needs.
• Collaborate on and share dashboards effectively.

This instructor-led, live training in Poland (online or onsite) is aimed at data analysts and data scientists who wish to use Metabase to collect, query, and visualize data for business intelligence analysis and reporting.

By the end of this training, participants will be able to:

• Set up and install Metabase to start building data visualizations and dashboards.
• Learn how to query, aggregate, and visualize data in Metabase.
• Use the features and tools in Metabase to write SQL queries.
• Build analytics charts and dashboards to get business insights.
• Know the best practices and tips on using Metabase and resolving common issues.

This instructor-led, live training in Poland (online or onsite) is aimed at data scientists and developers who wish to use Modin to build and implement parallel computations with Pandas for faster data analysis.

By the end of this training, participants will be able to:

• Set up the necessary environment to start developing Pandas workflows at scale with Modin.
• Understand the features, architecture, and advantages of Modin.
• Know the differences between Modin, Dask, and Ray.
• Perform Pandas operations faster with Modin.
• Implement the entire Pandas API and functions.

Microsoft Fabric is a unified analytics platform that brings together data engineering, data integration, data warehousing, data science, real-time analytics, and business intelligence under one umbrella.

This instructor-led, live training (online or onsite) is aimed at intermediate-level data professionals who wish to leverage Microsoft Fabric to build modern data solutions with integrated analytics, governance, and visualization tools.

By the end of this training, participants will be able to:

• Understand the components of Microsoft Fabric and how they integrate with the Microsoft ecosystem.
• Create and manage Fabric Workspaces with proper access control.
• Build and manage Lakehouses to centralize and analyze data.
• Use notebooks for exploratory analysis and transformation using Python and SQL.
• Create and automate data flows using visual pipelines.
• Model and manage data using the Data Warehouse and Semantic Model layers.
• Design and publish interactive dashboards with Power BI in Fabric.

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.

Szkolenie obejmuje kluczowe narzędzia wykorzystywane w pracy analitycznej i data science:
NumPy (operacje tablicowe), Pandas (analiza danych tabelarycznych) oraz biblioteki do wizualizacji.
Moduły prowadzą uczestnika od podstaw przetwarzania danych po tworzenie wykresów
i eksploracyjną analizę zbiorów danych (EDA)

Audience

Format of the course

By the end of this training, participants will be able to:

In this instructor-led, live training, participants will learn how to manipulate and visualize data using the tools included in the Tidyverse.

The Tidyverse is a collection of versatile R packages for cleaning, processing, modeling, and visualizing data. Some of the packages included are: ggplot2, dplyr, tidyr, readr, purrr, and tibble.

• Beginners to the R language
• Beginners to data analysis and data visualization

• Part lecture, part discussion, exercises and heavy hands-on practice

• Perform data analysis and create appealing visualizations
• Draw useful conclusions from various datasets of sample data
• Filter, sort and summarize data to answer exploratory questions
• Turn processed data into informative line plots, bar plots, histograms
• Import and filter data from diverse data sources, including Excel, CSV, and SPSS files