Data Analyst
Data analyst
About This Course
This course is designed for beginner to expert level with the tools to like SQL. Python, Power BI, Tableau and Excel with real-world projects, students will gain hands-on experience in transforming raw data into actionable insights.
What you'll learn
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Understand the role of a data analyst in business
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Collect, clean, and manipulate structured and unstructured data.
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Apply statistical and analytical techniques to interpret data.
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Write SQL queries for data extraction and reporting.
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Use Python (pandas, NumPy, matplotlib, seaborn) for data analysis.
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Create interactive dashboards using Power BI/Tableau.
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Communicate findings with clear reports and data visualizations.
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Work on real-world projects to build a professional portfolio.
Course Curriculum
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Introduction to Data Analytics
read- What is Data Analytics?
- Data Analyst roles and responsibilities
- Types of analytics: Descriptive, Diagnostic, Predictive, Prescriptive
- Overview of tools (Excel, SQL, Python, Power BI/Tableau)
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Excel for Data Analysis
read- Data cleaning and preparation
- Functions & formulas (VLOOKUP, INDEX-MATCH, Pivot Tables)
- Data visualization in Excel (charts, dashboards)
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SQL for Data Extraction
read- Introduction to databases and SQL
- Basic queries (SELECT, WHERE, ORDER BY)
- Joins, subqueries, and aggregations
- Window functions and CTEs
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Statistics & Data Analysis Fundamentals
read- mean, median, mode, variance, std dev
- Probability basics
- Hypothesis testing (t-test, chi-square)
- Correlation & regression analysis
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Python for Data Analysis
read- Introduction to Python and Jupyter Notebook
- Data cleaning and preprocessing
- Data visualization (matplotlib, seaborn, plotly)
- Exploratory Data Analysis (EDA)
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Data Visualization & Reporting
read- Introduction to BI tools (Power BI/Tableau)
- Building dashboards & reports
- Data storytelling techniques
- Publishing and sharing reports
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Advanced Analytics & Case Studies
read- Time series analysis basics
- Introduction to machine learning concepts for analysts
- Business case studies (marketing, sales, finance, operations)
Frequently Asked Questions
No, Python and SQL are taught from basics.
You can apply for Data Analyst, Business Analyst, Reporting Analyst, and Junior Data Scientist roles.
Yes, through assignments, projects, and case studies with real datasets.
Data Analyst focuses on analyzing and visualizing existing data for insights, while Data Science includes predictive modeling and machine learning.
Excel, SQL, Python, and Power BI/Tableau (depending on track).
Yes, the course is beginner-friendly with step-by-step guidance.
Prerequisites
- Basic computer skills
- Familiarity with MS Excel recommended (not mandatory)
- No prior programming experience required (Python & SQL taught from basics)
- Interest in working with data
Course Includes:
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7 Topics
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7 Lessons
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7 Articles
