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9 important plots in data science

Data Science Dojo

KS Plot (Kolmogorov-Smirnov Plot): The KS Plot is a powerful tool for comparing two probability distributions. This plot is particularly useful for tasks like hypothesis testing, anomaly detection, and model evaluation. Explore, analyze, and visualize data using Power BI Desktop to make data-driven business decisions.

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A Guide to Choose the Best Data Science Bootcamp

Data Science Dojo

Tools like Tableau, Power BI, and Python libraries such as Matplotlib and Seaborn are commonly taught. Statistics : Fundamental statistical concepts and methods, including hypothesis testing, probability, and descriptive statistics. R : Often used for statistical analysis and data visualization.

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Data Analysis vs. Data Visualization – More Than Just Pretty Charts

Pickl AI

From website clicks and social media interactions to sales figures and scientific measurements, information pours in from every direction. Data Analysis is the systematic process of inspecting, cleaning, transforming, modelling, and interpreting data to discover useful information, draw conclusions, and support decision-making.

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Popular Statistician certifications that will ensure professional success

Pickl AI

Programs like Pickl.AI’s Data Science Job Guarantee Course promise data expertise including statistics, Power BI , Machine Learning and guarantee job placement upon completion. It emphasises probabilistic modeling and Statistical inference for analysing big data and extracting information. Data Science Bootcamp Pickl.AI

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Data Scientist Salary in India’s Top Tech Cities

Pickl AI

Since there is a growing inclination towards online purchases, companies need to harness all the information which can later be used to formulate consumer-centric strategies. Data Scientists will play an integral role in this, and so, it has led to the rising employment of Data Scientists.

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The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

Data scientists, on the other hand, extract valuable information from complex datasets to make data-driven decisions. At the core of Data Science lies the art of transforming raw data into actionable information that can guide strategic decisions. Statistical Analysis: Hypothesis testing, probability, regression analysis, etc.

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How to Build a Data Analyst Portfolio?

Pickl AI

Data Visualization: Create compelling and informative Data Visualizations. In your data analyst portfolio, you should include a combination of projects, descriptions, technical details, and personal information to showcase your skills and expertise effectively. What to include in your portfolio?