What you'll learn
Data Analytics Course — About the Course
Data Analytics is a career-oriented course that teaches you how to collect, clean, analyze, visualize, and interpret data to make better business decisions.
🔹 What You Will Learn
- Excel & Advanced Excel – Data cleaning, formulas, Pivot Tables, dashboards
- SQL – Database handling and querying
- Python for Data Analytics – Pandas, NumPy and data analysis
- Power BI – Interactive dashboards and reports
- Data Visualization – Charts, graphs and business dashboards
- Statistics Basics – Understanding trends, patterns and relationships
- Real-World Projects – Practical analysis using business datasets
- AI Tools for Analytics – Using modern AI tools to improve data analysis and reporting
🎯 Career Opportunities
After completing the course, students can explore roles such as:
Data Analyst | Business Analyst | MIS Analyst | Reporting Analyst | BI Analyst | Junior Data Analyst
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Course Syllabus
DATA ANALYTICS COURSE SYLLABUS
Module 1: Introduction to Data Analytics
- What is Data Analytics?
- Types of Data Analytics
- Descriptive Analytics
- Diagnostic Analytics
- Predictive Analytics
- Prescriptive Analytics
- Data Analytics Life Cycle
- Data Collection & Data Sources
- Structured & Unstructured Data
- Real-world applications of Data Analytics
Module 2: MS Excel for Data Analytics
- Excel Interface & Data Entry
- Data Cleaning & Formatting
- Sort & Filter
- Conditional Formatting
- Important Excel Functions
- IF, SUMIF, COUNTIF
- VLOOKUP, XLOOKUP
- INDEX & MATCH
- TEXT & DATE Functions
- Pivot Table & Pivot Chart
- Data Validation
- What-If Analysis
- Advanced Excel
- Creating Interactive Dashboards
Module 3: Statistics for Data Analytics
- Mean, Median & Mode
- Range, Variance & Standard Deviation
- Percentage & Ratio
- Probability Basics
- Correlation
- Regression Basics
- Data Distribution
- Outliers
- Interpretation of Statistical Results
Module 4: SQL for Data Analytics
- Introduction to Database & SQL
- Database & Tables
- SELECT, WHERE, ORDER BY
- GROUP BY & HAVING
- Aggregate Functions
- INSERT, UPDATE & DELETE
- Joins
- INNER JOIN
- LEFT JOIN
- RIGHT JOIN
- Subqueries
- CASE Statements
- SQL Functions
- Practical Data Analysis Using SQL
Module 5: Python for Data Analytics
- Introduction to Python
- Variables & Data Types
- Operators
- Conditions & Loops
- Functions
- Lists, Tuples, Sets & Dictionaries
- Introduction to NumPy
- Introduction to Pandas
- DataFrames & Series
- Importing Excel/CSV Data
- Data Cleaning with Pandas
- Data Filtering & Transformation
Module 6: Data Visualization
- Principles of Data Visualization
- Charts & Graphs
- Bar Chart
- Line Chart
- Pie Chart
- Scatter Plot
- Histogram
- Interactive Visualizations
- Choosing the Right Chart
- Creating Professional Reports
Module 7: Power BI
- Introduction to Power BI
- Power BI Desktop
- Importing Data
- Power Query
- Data Cleaning & Transformation
- Data Modeling
- Relationships
- DAX Basics
- Calculated Columns & Measures
- Charts & Visuals
- Filters & Slicers
- Interactive Dashboard Creation
- Publishing & Sharing Reports
Module 8: AI for Data Analytics
- Introduction to AI in Data Analytics
- AI-assisted Data Cleaning
- AI for Excel Formulas
- AI for Data Interpretation
- AI-assisted SQL Queries
- AI-assisted Python Analysis
- Generating Insights & Reports
- AI-based Dashboard Assistance
- Responsible Use of AI
Module 9: Real-World Projects
Students work on practical datasets such as:
- Sales Data Analysis
- Customer Data Analysis
- Financial Data Analysis
- HR/Employee Data Analysis
- Marketing Data Analysis
- Business Performance Dashboard
- Final Data Analytics Project
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