
Data is the new gold — and Data Analytics is how organizations unlock its value. This course is designed as a step-by-step roadmap, covering everything from foundational statistics and SQL to data visualization, BI tools, and business storytelling.
You’ll learn to:
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Collect, clean, and prepare datasets for analysis.
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Perform statistical tests and regression analysis.
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Create impactful visualizations using Excel, Matplotlib, Seaborn, Tableau, and Power BI.
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Translate data insights into business strategies and KPIs.
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Work with cloud-based tools like BigQuery, Snowflake, and AWS S3.
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Build a strong portfolio with real-world projects.
By the end, you’ll have both the technical expertise and business acumen needed to become a successful Data Analyst.
Resources
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Python Data Analysis Libraries (Pandas, NumPy)
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SQL Cheat Sheets
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Tableau & Power BI Quick Start Guides
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Cloud Data Tools (BigQuery, Snowflake)
What Will You Learn?
- Foundations of mathematics & statistics for analytics.
- Programming with Python (Pandas, NumPy) & R.
- Work with SQL for querying and managing data.
- Perform data cleaning, wrangling, and feature engineering.
- Build impactful visualizations in Excel, Seaborn, Tableau, and Power BI.
- Apply hypothesis testing & regression analysis.
- Gain business acumen: KPIs, problem framing, and strategy.
- Master storytelling with data for non-technical audiences.
- Work on real-world & Kaggle projects.
- Explore cloud services for analytics workflows.