Data Science Dojo

JANUARY 16, 2023

Put more concretely, data analysis involves sifting through data, modeling it, and transforming it to yield information that guides strategic decision-making. For businesses, data analytics can provide highly impactful decisions with long-term yield. The data analysis process The process includes five key steps: 1.

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Pickl AI

NOVEMBER 4, 2024

Statistics Understand descriptive statistics (mean, median, mode) and inferential statistics (hypothesis testing, confidence intervals). These concepts help you analyse and interpret data effectively. It offers simple and efficient tools for data mining and Data Analysis.

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Pickl AI

OCTOBER 14, 2024

Role in Extracting Insights from Raw Data Raw data is often complex and unorganised, making it difficult to derive useful information. Data Analysis plays a crucial role in filtering and structuring this data. Techniques Hypothesis Testing: Determining whether enough evidence supports a specific claim or hypothesis.

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Pickl AI

MAY 29, 2024

Mastering programming, statistics, Machine Learning, and communication is vital for Data Scientists. A typical Data Science syllabus covers mathematics, programming, Machine Learning, data mining, big data technologies, and visualisation. Domain-specific knowledge enhances relevance.

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Pickl AI

AUGUST 27, 2024

This community-driven approach ensures that there are plenty of useful analytics libraries available, along with extensive documentation and support materials. For Data Analysts needing help, there are numerous resources available, including Stack Overflow, mailing lists, and user-contributed code.

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Pickl AI

SEPTEMBER 23, 2024

Applications of Data Science Data Science is not confined to one sector; its applications span multiple industries, transforming organisations’ operations. From healthcare to marketing, Data Science drives innovation by providing critical insights.

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AWS Machine Learning Blog

JUNE 26, 2024

Financial analysts and research analysts in capital markets distill business insights from financial and non-financial data, such as public filings, earnings call recordings, market research publications, and economic reports, using a variety of tools for data mining. Data exploration on stock data is done using Athena.

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