What will you learn in Google Data Analysis with Python Specialization course
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Use Python for practical data analysis tasks.
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Work with libraries such as Pandas and NumPy to manipulate datasets.
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Clean, transform, and prepare data for analysis.
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Perform exploratory data analysis (EDA) to uncover patterns and trends.
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Create visualizations using Python tools.
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Apply data-driven insights to real-world business problems.
Program Overview
Python Foundations for Data Analysis
⏳ 3–4 weeks
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Learn Python basics relevant to data analysis.
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Understand variables, data structures, and control flow.
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Work with Jupyter Notebooks for interactive coding.
Data Manipulation with Pandas and NumPy
⏳ 4–5 weeks
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Load and explore datasets using Pandas.
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Clean data by handling missing values and duplicates.
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Perform filtering, grouping, and aggregation operations.
Exploratory Data Analysis (EDA)
⏳ 3–4 weeks
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Identify patterns, trends, and anomalies in datasets.
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Apply descriptive statistics.
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Interpret findings to support decision-making.
Data Visualization and Reporting
⏳ 3–4 weeks
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Create visualizations using Python libraries.
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Communicate insights clearly to stakeholders.
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Build simple analysis reports.
Get certificate
Job Outlook
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Highly relevant for aspiring Data Analysts and Business Analysts.
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Python is one of the most in-demand skills in data careers.
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Valuable across industries including tech, retail, healthcare, and finance.
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Strong stepping stone toward advanced data science and machine learning roles.
