Designed for students and early professionals preparing for data analytics roles with practical training and real-world projects.
For students and professionals building real-world data analytics skills.
Module 1. Course Introduction
Day 01: Introduction to Data Science & Analytics
- Introduction to Data Science
- Scope of Data Science
- Data Science methodology
- Industry applications
Module 2. Python For Data Science
Day 02: Introduction to Python, Why Python, Variables, Operators, Strings, Indexing
- Python fundamentals
- Variables and data types
- Basic operators
- String manipulation and indexing
Day 03: Data Structures, Functions, Creating Function, Calling a function, Function Parameter
- Lists, dictionaries, tuples, and sets
- Function definition and calling
- Function parameters and return values
- Function scope
Day 04: Lambda Function, Conditional Statement, Loops and it's Control Statement
- Lambda functions
- Conditional statements (if, elif, else)
- Loops (for, while)
- Loop control statements (break, continue, pass)
Day 05: NumPy, Pandas for Data Handling
- NumPy arrays and operations
- Pandas DataFrames and Series
- Data manipulation with Pandas
- Data cleaning and preprocessing
Day 06: Matplotlib, Seaborn for Data Visualization
- Basic plotting with Matplotlib
- Advanced visualizations with Seaborn
- Customizing plots
- Creating interactive visualizations
Module 3. Statistics For Data Science
Day 07: Introduction to Statistics, Descriptive Statistics, Sample, Population, Major of Central Tendency
- Fundamentals of statistics
- Descriptive statistics
- Population vs. sample
- Measures of central tendency (mean, median, mode)
Day 08: Standard Deviation, Variance, Range, IQR, Outliers, Correlation, Covariance Skewness, Kurtosis
- Measures of dispersion
- Interquartile range and outlier detection
- Correlation and covariance
- Distribution characteristics (skewness, kurtosis)
Day 09: Probability, Probability distributions, Central Limit Theorem, Binomial & Normal Distribution
- Basic probability concepts
- Common probability distributions
- Central Limit Theorem
- Binomial and normal distributions
Day 10: Type I & Type II Error, T-test, Z-test, Hypothesis Testing
- Hypothesis testing fundamentals
- Type I and Type II errors
- T-tests and z-tests
- Practical applications of hypothesis testing
Module 4. Mini Project
Day 11: Data Analysis & Visualization
- Exploratory data analysis
- Data visualization techniques
- Insight extraction from data
- Mini project implementation
Module 5. SQL
Day 12: Basic of Database & its Types, Data Types, Operators, Create and Insert
- Database fundamentals
- SQL data types
- SQL operators
- CREATE and INSERT statements
Day 13: Drop, Truncate, Delete, Alter, Update, Select, Range, Operator, In,Wildcard
- Data manipulation commands
- Data definition language (DDL)
- SELECT statements and filtering
- Wildcard operators
Day 14: Like, Clause, Constraint, Aggregation Function, Group by, Order by
- LIKE operator and pattern matching
- SQL constraints
- Aggregation functions (SUM, AVG, COUNT, etc.)
- GROUP BY and ORDER BY clauses
Day 15: Having, Joins, Case, Complex Queries, Doubt Clearing
- HAVING clause
- SQL JOINs (INNER, LEFT, RIGHT, FULL)
- CASE statements
- Advanced SQL queries
Module 6. Power BI
Day 16: Power BI Platform, Process Flow
- Power BI ecosystem
- Power BI Desktop interface
- Data workflow in Power BI
- Connecting to data sources
Day 17: Features, Dataset, and Bias
- Power BI key features
- Dataset creation and management
- Understanding data bias
- Data preparation techniques
Day 18: Pivoting, Query Group, DAX Function
- Data pivoting operations
- Query organization
- DAX function fundamentals
- Creating calculated measures
Day 19: Formula, Charts, Reports and Dashboards
- DAX formulas and expressions
- Chart types and selection
- Report creation best practices
- Dashboard design and deployment
Module 7. Major Project
Day 20: Database to Dashboard: Project Implementation with SQL, Tableau & Power BI
- End-to-end business intelligence project
- Database design and implementation
- Data visualization with Tableau and Power BI
- Creating interactive business dashboards
Module 8. Advanced Excel
Day 21: Microsoft Excel Overview, Formatting Excel, Shortcuts and Basic Formulas
- Microsoft Excel Overview
- Formatting Excel
- Shortcuts and Basic Formulas
Day 22: Sorting Data, Filtering Data, Charts, Column Chart, Pie Chart
- Sorting Data
- Filtering Data
- Charts
- Column Chart
- Pie Chart
Day 23: Pivot Tables, Lookup Function, Vlookup, Hlookup, Match Function
- Pivot Tables
- Lookup Function
- Vlookup
- Hlookup
- Match Function
Day 24: VBA, Macros, Dashboards, Interview Questions
- VBA
- Macros
- Dashboards
- Interview Questions
