IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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Pickl AI

AUGUST 9, 2024

Big Data Technologies and Tools A comprehensive syllabus should introduce students to the key technologies and tools used in Big Data analytics. Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers.

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Pickl AI

MAY 31, 2023

Explore Machine Learning with Python: Become familiar with prominent Python artificial intelligence libraries such as sci-kit-learn and TensorFlow. Tools such as Matplotlib, Seaborn, and Tableau may help you in creating useful visualisations that make challenging data more readily available and understandable to others.

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Pickl AI

JULY 10, 2023

. · Big Data Analytics: R has solutions for handling large-scale datasets and performing distributed computing. Packages like dplyr, data.table, and sparklyr enable efficient data processing on big data platforms such as Apache Hadoop and Apache Spark.

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ODSC - Open Data Science

MARCH 5, 2025

From the Early Days of Data Science to Todays Complex Ecosystem Marcks journey into data science began nearly 20 years ago when the field was still in its infancy. In the early 2010s, the rise of Hadoop and cloud computing transformed the industry, introducing data practitioners to new challenges in scalability and infrastructure.

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