Top 10 Data Science Software for Eastern Europe

2026. Data science service Amazon SageMaker launched AI agent



Amazon SageMaker AI now includes a model tuning agent. It helps you prepare your data, select the right model, evaluate its quality using LLM-as-an-expert metrics, and find the most cost-effective way to deploy it to Amazon Bedrock or SageMaker AI endpoints. The agent is available in Amazon SageMaker Studio notebooks along with the Kiro coding agent. Users can also use the agent's skills in their preferred development environment, such as Visual Studio or Cursor. The interface allows you to use a variety of coding agents, including Kiro, Claude Code, and CoPilot, to optimize popular model families such as Amazon Nova, Llama, Qwen, and GPT-OSS.


2025. Google Colab gets AI assistant



Google Colab, a cloud-based data science tool, has added a new feature - Data Science Agent. It helps users quickly clean data, visualize trends, and gain insights from uploaded datasets. The assistant can also search for anomalies in APIs, analyze customer data, and write SQL queries. Users simply upload a file and ask the agent a question. Data Science Agent is powered by the Gemini 2.0 AI model, along with tools for data analysis and cleaning. Currently, the agent supports CSV, JSON, and .txt files up to 1 GB in size. The assistant is available for free, but with some computing power limitations. To address these limitations, Google offers paid plans starting at $9.99 per month.


2019. JupyterLab - the next generation of Jupyter Notebook



The open-source project Jupyter that develops Jupyter Notebook, has unveiled its future replacement, JupyterLab. It's a fully-fledged development environment where data scientists can simultaneously work with notebooks, files, terminals and code editors. JupyterLab is similar to VS Code or PyCharm: file manager pane on the left, and several open tabs (notebooks, scripts and terminals) in the center. It allows you to work with multiple notebooks simultaneously, edit .py, .md, and .json files - in other words, it offers something akin to an IDE while remaining within the Jupyter ecosystem. The classic Jupyter Notebook will still be supported, but new features will be added to JupyterLab.