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How To Switch To Data Science From Your Current Career Path?

Knowledge Hut

Developing technical skills is essential, starting with foundational knowledge in mathematics, including calculus and linear algebra, which underpin machine learning and deep learning concepts. Through the article, we will learn what data scientists do, and how to transits to a data science career path.

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Top Data Science and Machine Learning Interview Questions 2022

U-Next

A multidisciplinary field called Data Science involves unprocessed data mining, its analysis, and discovering patterns utilized to extract meaningful information. The fundamental building blocks of Data Science are Statistics, Machine Learning, Computer Science, Data Analysis, Deep Learning, and Data Visualization. .

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Top 12 Data Engineering Project Ideas [With Source Code]

Knowledge Hut

If you want to break into the field of data engineering but don't yet have any expertise in the field, compiling a portfolio of data engineering projects may help. Data pipeline best practices should be shown in these initiatives. However, the abundance of data opens numerous possibilities for research and analysis.

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50 Artificial Intelligence Interview Questions and Answers [2023]

ProjectPro

Let's understand where Data Science belongs in the space of Artificial Intelligence. The estimator automatically performs the algorithm selection as well as the hyperparameter tuning Auto-Keras : To recall, Keras is an open-source library that provides a Python interface into the world of Artificial Intelligence, especially Tensorflow.

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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

This project is an opportunity for data enthusiasts to engage in the information produced and used by the New York City government. Learn how to use various big data tools like Kafka, Zookeeper, Spark, HBase, and Hadoop for real-time data aggregation. Strong proficiency in using SQL for data sourcing.

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Data Science Salary In 2022

U-Next

Data Science is an interdisciplinary field that blends programming skills, domain knowledge, reasoning skills, mathematical and statistical skills to generate value from a large pool of data. The first step is capturing data, extracting it periodically, and adding it to the pipeline. Skill requirements for Data Science.