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Introduction to applied data science 101: Key concepts and methodologies 

Data Science Dojo

Statistical analysis and hypothesis testing Statistical methods provide powerful tools for understanding data. An Applied Data Scientist must have a solid understanding of statistics to interpret data correctly.

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Skills Required for Data Scientist: Your Ultimate Success Roadmap

Pickl AI

Summary: Data Science is becoming a popular career choice. 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.

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How To Learn Python For Data Science?

Pickl AI

Its robust ecosystem of libraries and frameworks tailored for Data Science, such as NumPy, Pandas, and Scikit-learn, contributes significantly to its popularity. Moreover, Python’s straightforward syntax allows Data Scientists to focus on problem-solving rather than grappling with complex code.

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Why Python is Essential for Data Analysis

Pickl AI

Discover the reasons behind Python’s dominance in data analysis, from its user-friendly syntax and extensive libraries to its scalability and community support, making it the go-to language for data scientists and analysts worldwide. It is particularly useful for regression analysis and hypothesis testing.

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Exploring Different Types of Data Analysis: Methods and Applications

Pickl AI

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. The primary purpose of EDA is to explore the data without any preconceived notions or hypotheses.

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Why and How can you do a Masters in Data Science in India?

Pickl AI

Understanding these aspects will help aspiring Data Scientists make informed decisions about their educational journey. Why Pursue a Master’s in Data Science? Pursuing a Master’s in Data Science opens doors to numerous opportunities in a rapidly growing field.

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Statistical Analysis- Types, Methods & Examples

Pickl AI

There are other types of Statistical Analysis as well which includes the following: Predictive Analysis: Significantly, it is the type of Analysis useful for forecasting future events based on present and past data. Effectively, the test result can help nullify the hypothesis, in which case it becomes a null hypothesis or hypothesis 0.