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Discover Interoperability between Python, MATLAB and R Languages

Pickl AI

Python offers rich libraries like Pandas and TensorFlow for Data Wrangling , Machine Learning , and Web-Based Applications. MATLAB is ideal for matrix-heavy computations, simulations, and engineering tasks, while R shines in statistical analysis and visualisations.

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Top 10 Data Science Interviews Questions and Expert Answers

Pickl AI

Data Wrangling and Cleaning Interviewers may present candidates with messy datasets and evaluate their ability to clean, preprocess, and transform data into usable formats for analysis. What is the Central Limit Theorem, and why is it important in statistics?

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Roadmap to Learn Data Science for Beginners and Freshers in 2023

Becoming Human

There is a position called Data Analyst whose work is to analyze the historical data, and from that, they will derive some KPI s (Key Performance Indicators) for making any further calls. For Data Analysis you can focus on such topics as Feature Engineering , Data Wrangling , and EDA which is also known as Exploratory Data Analysis.

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Strategies for Transitioning Your Career from Data Analyst to Data Scientist–2024

Pickl AI

Data Analyst to Data Scientist: Level-up Your Data Science Career The ever-evolving field of Data Science is witnessing an explosion of data volume and complexity. Familiarize yourself with their services for data storage, processing, and model deployment.

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The Evolving Role of the Modern Data Practitioner

ODSC - Open Data Science

In the ever-expanding world of data science, the landscape has changed dramatically over the past two decades. Once defined by statistical models and SQL queries, todays data practitioners must navigate a dynamic ecosystem that includes cloud computing, software engineering best practices, and the rise of generative AI.

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15 Fan-Favorite Speakers & Instructors Returning for ODSC East 2025

ODSC - Open Data Science

With over 30 years in techincluding key roles at Hugging Face, AWS, and as a startup CTOhe brings unparalleled expertise in cloud computing and machine learning. As the author of *Hands-On Data Analysis with Pandas* (now in its second edition), she is a recognized expert in making data actionable.