Data Analytics with Python & Power BI Course in Jaipur
Turn business questions into clear analysis, reports and dashboards. Work through data cleaning, Excel, SQL, Python, statistics and business-intelligence tools, then explain the decisions supported by your findings.
- Practical learning
- Project practice
- Jaipur
Data Analytics with Python & Power BI
Build your foundation in Data Analytics with Python & Power BI
Turn business questions into clear analysis, reports and dashboards. Work through data cleaning, Excel, SQL, Python, statistics and business-intelligence tools, then explain the decisions supported by your findings.
The dedicated curriculum progresses from Excel and SQL foundations to Python analysis with NumPy and Pandas, charting with Matplotlib and Seaborn, and reporting with Power BI, Power Query and DAX. Each tool supports a practical analyst workflow: prepare data, analyse it, communicate results and review the business question.
Source-listed projects cover sales, e-commerce, customer behaviour, HR, finance and marketing analysis. The existing Tableau reporting coverage is retained from the reviewed static syllabus alongside the newer source curriculum.
Who can join?
Students, graduates and working professionals interested in analytical work. Basic computer and spreadsheet familiarity helps; programming topics start with Python foundations.
Skills and tools
Course curriculum
Explore the published learning outline below. Confirm the detailed syllabus and module coverage for your chosen batch with the course team.
Introduction to Data Analytics
Understand the analyst workflow, data types and how a business question guides data collection and analysis.
- Introduction to Data Analytics
- Types of Data Analytics
- Data Analytics Lifecycle
- Role of a Data Analyst
- Data Analytics vs Data Science
- Understanding Data Types
- Structured vs Unstructured Data
- Data Sources and Data Collection
- Business Problems and Data-Driven Decisions
- Data Analytics Career Opportunities
Microsoft Excel Fundamentals
Build spreadsheet foundations with formulas, references, formatting, filters and validation.
- Introduction to Microsoft Excel
- Excel Interface and Workbook Basics
- Rows, Columns and Cells
- Data Entry and Formatting
- Basic Excel Formulas
- Relative and Absolute Cell References
- Sorting and Filtering Data
- Conditional Formatting
- Data Validation
- Working with Multiple Worksheets
Advanced Excel for Data Analysis
Use logical, lookup, text, date, statistical and dynamic-array functions to prepare useful analysis.
- Logical Functions
- Lookup Functions
- XLOOKUP and VLOOKUP
- INDEX and MATCH
- Text Functions
- Date and Time Functions
- Mathematical and Statistical Functions
- Error Handling Functions
- Dynamic Arrays
- Advanced Excel Data Analysis
Data Cleaning and Preparation in Excel
Identify missing or duplicate values and standardise text, dates and numbers before analysis.
- Introduction to Data Cleaning
- Identifying Missing Data
- Removing Duplicate Records
- Text to Columns
- Find and Replace
- Cleaning Text Data
- Handling Dates and Numbers
- Data Validation Techniques
- Data Standardization
- Preparing Data for Analysis
Pivot Tables and Excel Dashboards
Summarise data with pivot tables and charts, then create an interactive Excel dashboard.
- Introduction to Pivot Tables
- Creating Pivot Tables
- Pivot Table Fields and Layouts
- Grouping and Filtering Data
- Calculated Fields
- Pivot Charts
- Slicers and Timelines
- Dashboard Design Principles
- Creating Interactive Excel Dashboards
- Excel Dashboard Project
SQL Fundamentals
Understand relational tables and practise queries, filters, sorting, aliases and table definitions.
- Introduction to SQL and Databases
- Understanding Relational Databases
- Tables, Rows and Columns
- SELECT Statements
- WHERE Clause
- ORDER BY and LIMIT
- DISTINCT and Aliases
- SQL Data Types
- Creating and Modifying Tables
- SQL Fundamentals Practice
Advanced SQL for Data Analytics
Combine and summarise data with joins, subqueries, common table expressions and window functions.
- Aggregate Functions
- GROUP BY and HAVING
- SQL Joins
- INNER JOIN
- LEFT and RIGHT JOIN
- Subqueries
- Common Table Expressions
- Window Functions
- CASE Statements
- Advanced SQL Data Analysis Project
Python Fundamentals for Data Analytics
Learn Python foundations, Jupyter Notebook, collections, functions and file handling for analysis.
- Introduction to Python
- Installing Python and Jupyter Notebook
- Variables and Data Types
- Operators and Expressions
- Conditional Statements
- Loops
- Functions
- Lists, Tuples and Sets
- Dictionaries
- Working with Python Files
Python Libraries for Data Analysis
Use NumPy and Pandas to import, clean, select, group and analyse tabular data.
- Introduction to NumPy
- NumPy Arrays and Operations
- Introduction to Pandas
- Series and DataFrames
- Importing CSV and Excel Data
- Data Selection and Filtering
- Data Cleaning with Pandas
- Handling Missing Values
- Grouping and Aggregation
- Data Analysis with Pandas Project
Data Visualization with Python
Choose and customise charts with Matplotlib and Seaborn to communicate analytical findings.
- Introduction to Data Visualization
- Matplotlib Fundamentals
- Line Charts
- Bar Charts
- Pie Charts
- Histograms
- Scatter Plots
- Customizing Charts
- Introduction to Seaborn
- Python Data Visualization Project
Statistics for Data Analytics
Explore descriptive statistics, probability, distributions and correlation. The retained static syllabus also introduces sampling and hypothesis-testing concepts.
- Introduction to Statistics
- Types of Data and Variables
- Measures of Central Tendency
- Mean, Median and Mode
- Measures of Dispersion
- Variance and Standard Deviation
- Probability Fundamentals
- Normal Distribution
- Correlation and Relationships
- Statistical Analysis for Business Decisions
Power BI Fundamentals
Connect data, create models and visual reports, apply filters and publish Power BI reports.
- Introduction to Power BI
- Power BI Desktop Interface
- Connecting Data Sources
- Importing Excel and CSV Data
- Understanding Data Models
- Data Transformation Basics
- Creating Tables and Charts
- Filters and Slicers
- Report Design
- Publishing Power BI Reports
Power Query and DAX
Transform and combine data with Power Query, then define calculated columns, measures and time-intelligence calculations with DAX.
- Introduction to Power Query
- Data Cleaning with Power Query
- Merging Queries
- Appending Queries
- Data Transformation Techniques
- Introduction to DAX
- Calculated Columns
- Measures
- Time Intelligence Functions
- Advanced Power BI Calculations
Power BI Dashboards and Business Intelligence
Plan KPIs, interactive reports, drill-through navigation and business dashboards for sales and HR analysis.
- Dashboard Planning
- KPI Development
- Creating Interactive Reports
- Drill-Down and Drill-Through
- Bookmarks and Navigation
- Advanced Visualizations
- Business Performance Analysis
- Sales Analytics Dashboard
- HR Analytics Dashboard
- Complete Power BI Dashboard Project
Data Analytics Live Projects
Apply Excel, SQL, Python and Power BI workflows to source-listed business datasets and a final capstone.
- Sales Data Analysis Project
- E-Commerce Data Analytics Project
- Customer Behaviour Analysis
- HR Analytics Project
- Financial Data Analysis
- Marketing Campaign Analysis
- SQL Data Analysis Project
- Python Data Analytics Project
- Power BI Business Dashboard
- Final Data Analytics Capstone Project
Tableau visual analytics
Retained from the reviewed static syllabus: choose charts, filters and calculated fields, create Tableau dashboards and explore publishing workflows.
Project practice ideas
Use these examples to discuss suitable practice work with your trainer.
Business analysis workbook
Clean a dataset, create a pivot-based summary and explain the business findings.
Interactive reporting dashboard
Build a dashboard with clear measures and filters, and present the decisions it supports.
SQL data analysis project
Use joins, aggregations and analytical queries to answer questions from a relational business dataset.
Python data analytics project
Import and clean a dataset with Pandas, analyse it and visualise useful patterns with Python charting tools.
Sales and customer analysis
Explore sales, e-commerce or customer-behaviour data and present findings in an analyst report or dashboard.
Final data analytics capstone
Combine data preparation, analysis, visualisation and an explanation of business findings in a portfolio project.
Roles to explore
Build a portfolio and practise explaining your work. Role requirements depend on the employer, your skills and experience.
- Junior data analyst
- Reporting analyst
- Business intelligence trainee
Frequently asked questions
How is Data Analytics different from Data Science?
Data Analytics focuses on cleaning, querying, reporting, dashboards and communicating findings. Data Science goes further into predictive modelling and machine-learning techniques.
Does this Data Analytics course include Power BI?
Yes. The learning path includes Power BI relationships, DAX, reports and dashboards. Learners who want a narrower business-intelligence focus can also review the dedicated Power BI course page.
Can a beginner join the Data Analytics course?
Yes. The dedicated source curriculum begins with Excel, SQL and Python fundamentals and progresses to analysis, dashboards and projects. Basic computer familiarity and regular practice help.
What projects does the curriculum include?
Source-listed exercises include an Excel dashboard, SQL analysis, Pandas analysis, Python visualisation, Power BI dashboards and a final capstone. Business contexts include sales, e-commerce, customer behaviour, HR, finance and marketing.
Does the course include NumPy, Pandas and Python visualisation?
Yes. The Python modules include NumPy arrays, Pandas Series and DataFrames, data cleaning, grouping and aggregation, plus charts with Matplotlib and Seaborn.
Is Tableau still included alongside Power BI?
The existing Tableau reporting material is retained from the reviewed static syllabus. The dedicated LearnPress curriculum adds detailed Power BI, Power Query and DAX modules. Confirm the tools used for the selected batch.
Who is this course for?
Students, graduates and working professionals interested in analytical work. Basic computer and spreadsheet familiarity helps; programming topics start with Python foundations.
How can I confirm fees, duration and batch timings?
Contact Groot Academy for the current syllabus, fees, duration and available learning modes before enrolling. These details depend on the selected course and batch.
Ready to discuss Data Analytics with Python & Power BI?
Ask the course team about syllabus coverage, current batch timings, fees, duration and learning modes before you decide.