Data Analytics
Become a job-ready Data Analyst with Excel, SQL, Python, Power BI, and Tableau. Learn to clean, analyze, and visualize data, build interactive dashboards, and turn raw numbers into clear business insights that drive decisions — and ship real, portfolio-worthy analytics projects. Start free, go job-ready, and launch your career in data.
In short: This Data Analytics program is a 60–65 hour, fully online, job-ready course. You start with 15 hours of free foundations (analytics concepts & Excel, SQL, statistics, and Git) and continue into a 45–50 hour paid program covering advanced SQL, Python with Pandas & NumPy, data cleaning and wrangling, data visualization and dashboards with Power BI and Tableau, statistics and A/B testing, exploratory data analysis and data storytelling, and cloud analytics with BigQuery — finishing with an end-to-end analytics capstone, a portfolio, and full interview prep.
The Data Analytics course is designed to help learners master the complete analytics workflow — from raw data to clean, insightful dashboards and reports that drive business decisions — and become immediately employable as Data Analysts, Business Analysts, and BI Analysts.
This course covers Excel and spreadsheets, SQL for data analysis, Python with Pandas and NumPy, data cleaning and wrangling, data visualization and interactive dashboards with Power BI and Tableau, statistics and A/B testing, exploratory data analysis and data storytelling, and cloud analytics with BigQuery. Learners build real, portfolio-worthy analytics projects at every stage using hands-on, project-based learning.
By completing this training, participants will be well-prepared for Data Analyst, Business Analyst, and BI Analyst roles, with a polished portfolio, a strong resume, and interview readiness.
Course Highlights
- End-to-end coverage from Excel & SQL foundations to cloud analytics
- Analyze data with SQL and Python (Pandas & NumPy)
- Build interactive dashboards with Power BI and Tableau
- Apply statistics, A/B testing, and data storytelling
- Clean, wrangle, and explore real-world messy data
- Job-readiness: portfolio, resume, and interview prep
Learning Outcomes
- Analyze and summarize data with Excel, SQL, and Python
- Clean, transform, and prepare messy real-world datasets
- Build interactive dashboards and reports in Power BI and Tableau
- Apply statistics and A/B testing to answer business questions
- Perform exploratory data analysis and tell data-driven stories
- Run analytics in the cloud with BigQuery
Job Opportunities
- Data Analyst
- Business Analyst
- Business Intelligence (BI) Analyst
- Reporting / MIS Analyst
- Product / Marketing Analyst
- Analytics Associate
What You'll Build (Portfolio Projects)
- An Excel analysis workbook with pivot tables and charts
- SQL analysis queries on a real business database
- A Python data-cleaning and analysis notebook with Pandas
- Interactive Power BI and Tableau dashboards
- An end-to-end analytics capstone turning raw data into insights
Tools & Skills Covered
- Excel, Google Sheets, SQL
- Python, Pandas, NumPy, Matplotlib, Seaborn
- Power BI, Tableau, BigQuery, Git, statistics & A/B testing
Material Includes
- Class recordings
- Datasets & project starter files
- Certificate
Who Can Join
- IT Graduates & Freshers
- Aspiring Data & Business Analysts
- Career Switchers
Related Courses
Free Foundation — 15 Hours
Start learning for free. Build your core analytics, Excel, SQL, and statistics foundations before advancing to the job-ready Data Analytics program.
Estimated Time: 5 Hours
Learning Objectives:- Understand the data analytics workflow and roles
- Analyze data confidently in spreadsheets
- What data analytics is and the analyst workflow
- Excel formulas, functions, and data cleaning basics
- Pivot tables, charts, and lookup functions
- Build an Excel analysis workbook with pivot tables and charts
Estimated Time: 5 Hours
Learning Objectives:- Query and analyze data with SQL
- Answer business questions directly from databases
- SELECT, WHERE, GROUP BY, and ORDER BY
- Joins, keys, and relationships
- Aggregations, subqueries, and filtering for analysis
- Write SQL queries to analyze a real business dataset
Estimated Time: 3 Hours
Learning Objectives:- Apply core statistics to interpret data
- Think analytically about business problems
- Descriptive statistics: mean, median, spread
- Distributions, correlation, and outliers
- Framing questions and metrics that matter
- Summarize and interpret a dataset statistically
Estimated Time: 2 Hours
Learning Objectives:- Track your analysis code and notebooks with Git
- Collaborate and showcase your work on GitHub
- Repositories, commits, and branches
- Merging, pull requests, and conflict resolution
- Building a professional analytics GitHub profile
- Push your first analysis projects to GitHub
Paid Job-Ready Program — 45–50 Hours
Go from foundations to fully employable. Master advanced SQL, Python for analysis, data cleaning, Power BI and Tableau dashboards, statistics and A/B testing, and cloud analytics — everything you need to land your first data analyst job.
Estimated Time: 5 Hours
Learning Objectives:- Write advanced analytical SQL
- Answer complex business questions with data
- Window functions and common table expressions (CTEs)
- Advanced joins, CASE logic, and date functions
- Cohort, funnel, and time-series analysis in SQL
- Build an analytical SQL report with window functions
Estimated Time: 6 Hours
Learning Objectives:- Analyze data programmatically with Python
- Manipulate datasets with Pandas and NumPy
- Python essentials for analysts
- NumPy arrays and Pandas DataFrames
- Filtering, grouping, merging, and aggregating data
- Analyze a dataset end to end in a Pandas notebook
Estimated Time: 5 Hours
Learning Objectives:- Turn messy raw data into analysis-ready datasets
- Handle missing, duplicate, and inconsistent data
- Missing values, duplicates, and data types
- Reshaping, merging, and joining datasets
- Feature creation and data quality checks
- Clean and prepare a messy real-world dataset
Estimated Time: 5 Hours
Learning Objectives:- Build interactive dashboards in Power BI
- Model data and write DAX measures
- Connecting, transforming, and modeling data
- Visuals, filters, and interactive reports
- DAX measures and calculated columns
- Build an interactive business dashboard in Power BI
Estimated Time: 5 Hours
Learning Objectives:- Create compelling dashboards in Tableau
- Design reports that communicate insights clearly
- Connecting data and building worksheets
- Calculated fields, parameters, and filters
- Interactive dashboards and story points
- Build and publish an interactive Tableau dashboard
Estimated Time: 4 Hours
Learning Objectives:- Apply statistics to real business decisions
- Design and interpret A/B tests
- Hypothesis testing and confidence intervals
- A/B testing design and interpretation
- KPIs, business metrics, and experimentation
- Analyze an A/B test and recommend a decision
Estimated Time: 4 Hours
Learning Objectives:- Explore data to uncover patterns and insights
- Communicate findings with clear data stories
- EDA workflow with Pandas, Matplotlib, and Seaborn
- Visual best practices and chart selection
- Turning analysis into a persuasive narrative
- Run an EDA and present a data-driven story
Estimated Time: 3 Hours
Learning Objectives:- Automate reporting in Excel and Google Sheets
- Speed up recurring analysis tasks
- Advanced formulas, Power Query, and what-if analysis
- Dashboards and templates in Sheets
- Automating reports and connecting live data
- Build an automated reporting spreadsheet
Estimated Time: 5 Hours
Learning Objectives:- Analyze large datasets in the cloud
- Query data warehouses with SQL at scale
- Cloud data warehouses and BigQuery basics
- Querying large datasets efficiently
- Connecting BI tools to cloud data
- Analyze a large dataset in BigQuery and visualize it
Estimated Time: 6 Hours
Learning Objectives:- Ship a complete, portfolio-ready analytics project
- Prepare for the data analyst job search
- End-to-end capstone: data to dashboard to insights
- Portfolio, GitHub, and resume optimization
- Data analyst SQL, case-study, and interview prep
- Build and present an end-to-end analytics project
- Mock interviews and resume review