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Data science - IBM Developer
IBM Developer

Data science

Analyze structured and unstructured data to extract knowledge and insights.

Data science is the process of using algorithms, methods, and systems to extract knowledge and insights from structured and unstructured data. It can be used to make predictions and decisions using analytics and machine learning.

07 October 2025

Article

Agentic data scientists: Redefining the future of analytics

Discover the Agentic Data Scientist, a revolutionary tool that automates data science workflows using LangGraph and watsonx. Simply upload a CSV/Excel file, describe your analysis, and let the agent do the work. The AI-driven agent plans, codes, executes, reviews, and delivers results, streamlining your data science tasks with minimal human intervention.

Agentic data scientists: Redefining the future of analytics

19 August 2025

Article

From data to prediction: Building a robust predictive analytics pipeline

Predictive analytics pipelines empower teams to move from reactive to proactive operations. Developers must architect these systems to be efficient, transparent, and adaptable. By understanding the end-to-end flow of data, from raw data ingestion, through preprocessing and feature engineering, to PCA, to model deployment and prediction, developers can build solutions that provide valuable foresight, such as predicting employee stress before it impacts productivity.

From data to prediction: Building a robust predictive analytics pipeline

25 April 2025

Article

Build machine learning models with and without AutoML

Look at two ways to build predictive models, both with and without the help of AutoAI.

Build machine learning models with and without AutoML

Course

Coursera

Data analysis with Python

Get hands-on experience and learn important techniques for preparing your data for analysis. Then, learn how to gain a better understanding of your data through exploratory data analysis.

Data analysis with Python

Course

Coursera

Data analysis with R

Get hands-on experience and learn important techniques for preparing your data for analysis. Then, learn how to gain a better understanding of your data through exploratory data analysis.

Data analysis with R

Course

Coursera

Applied data science with R specialization

Build your data science skills with R and SQL. Master the ability to transform data into information and insights.

Applied data science with R specialization

11 December 2024

Article

Key scenarios and components of RAG Deployable Architecture

Explore IBM RAG DA to deploy secure, scalable, and customizable Retrieval Augmented Generation solutions with AI, Watsonx, and generative AI technologies.

Key scenarios and components of RAG Deployable Architecture

28 November 2024

Tutorial

Updating the knowledge base of a RAG DA chatbot

Learn how to update a RAG chatbot knowledge base with new documents in IBM Cloud to improve real-time accuracy and enhance chatbot performance.

Updating the knowledge base of a RAG DA chatbot

26 November 2024

Tutorial

Deploying RAG Solutions with elasticsearch Platinum and OpenShift

Learn how to deploy Retrieval-Augmented Generation with elasticsearch Platinum and Red Hat OpenShift on IBM Cloud for scalable GenAI applications.

Deploying RAG Solutions with ElasticSearch Platinum and OpenShift

07 October 2024

Tutorial

Accelerating Gen AI on IBM Cloud: Deployable Architectures

Discover how RAG Deployable Architecture on IBM Cloud maximizes Gen AI deployment speed, security, and compliance for enterprise solutions.

Accelerating Gen AI on IBM Cloud: Deployable Architectures

19 August 2024

Tutorial

Using different LLMs in watsonx.ai flows engine

Learn how to use various models with the watsonx.ai flows engine to create a custom flow for text completion with several different prompting techniques.

Using different LLMs in watsonx.ai flows engine

05 August 2024

Tutorial

Analyzing and forecasting with time series data using ARIMA models in Python

Learn about how ARIMA models can help you analyze and create forecasts from time series data. Learn how to create and assess ARIMA models using Python in a Jupyter notebook on IBM watsonx.ai platform.

Analyzing and forecasting with time series data using ARIMA models in Python
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Data science - IBM Developer