Pickl AI

JULY 18, 2023

With technological developments occurring rapidly within the world, Computer Science and Data Science are increasingly becoming the most demanding career choices. Moreover, with the oozing opportunities in Data Science job roles, transitioning your career from Computer Science to Data Science can be quite interesting.

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Pickl AI

APRIL 21, 2025

Key Takeaways Big Data focuses on collecting, storing, and managing massive datasets. Data Science extracts insights and builds predictive models from processed data. Big Data technologies include Hadoop, Spark, and NoSQL databases. Data Science uses Python, R, and machine learning frameworks.

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IBM Journey to AI blog

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. And you should have experience working with big data platforms such as Hadoop or Apache Spark.

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Pickl AI

AUGUST 21, 2023

This guide throws light on the roadmap to becoming a Data Scientist. Key Takeaways: Data Science is a multidisciplinary field bridging statistics, mathematics, and computer science to extract insights from data. Step 4: Data Wrangling and Visualization Data isn’t always in pristine formats.

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Pickl AI

MAY 17, 2023

Steps to Become a Data Scientist If you want to pursue a Data Science course after 10th, you need to ensure that you are aware the steps that can help you become a Data Scientist. Accordingly, make sure that you have Python and R as part of your high-school course or online course in Data Science.

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Pickl AI

JUNE 21, 2023

Gain knowledge in data manipulation and analysis: Familiarize yourself with data manipulation techniques using tools like SQL for database querying and data extraction. Also, learn how to analyze and visualize data using libraries such as Pandas, NumPy, and Matplotlib.

Data Scientist 52

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Pickl AI

SEPTEMBER 12, 2024

Key Components of Data Science Data Science consists of several key components that work together to extract meaningful insights from data: Data Collection: This involves gathering relevant data from various sources, such as databases, APIs, and web scraping.

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