Data Analytics Accelerator
Go from Excel user to data analyst in 8 weeks.
- Duration
- 8 weeks
- Duration
- Sessions
- 12
- Sessions
- Labs
- 8
- Labs
- Projects
- 2
- Projects
What You'll Be Able To Do
After completing this course, you will confidently:
- Write SQL queries to extract, filter, aggregate, and join data from relational databases
- Manipulate and clean datasets using Python with Pandas for reproducible analysis
- Build interactive dashboards in Power BI with filters, slicers, and drill-through navigation
- Apply advanced Excel techniques including pivot tables, VLOOKUP, INDEX/MATCH, and conditional formatting
- Calculate and interpret key business metrics — conversion rates, churn, retention, and cohort analysis
- Design data visualizations that communicate insights clearly to non-technical stakeholders
- Automate repetitive data tasks using Python scripts and SQL stored procedures
- Present data-driven recommendations to business stakeholders with structured storytelling
What You'll Build
Real portfolio projects that showcase your skills to employers.
Sales Performance Dashboard
Build an interactive Power BI dashboard analyzing sales data across regions, products, and time periods. Includes KPI cards, trend analysis, and drill-through pages for detailed exploration.
Interview value:
Dashboard skills are the primary screening criteria for data analyst roles. A polished Power BI dashboard is the strongest portfolio piece you can present.
Customer Segmentation Analysis
Use Python and SQL to segment customers by behavior, purchase patterns, and demographics. Present findings in a structured report with actionable recommendations for marketing and retention teams.
Interview value:
Customer segmentation demonstrates analytical thinking and the ability to translate data into business recommendations — exactly what hiring managers evaluate.
Course Curriculum
8 weeks of structured, hands-on learning.
1SQL Fundamentals
- Database concepts — tables, rows, columns, primary keys, foreign keys
- SELECT, WHERE, ORDER BY, and LIMIT
- Aggregate functions — COUNT, SUM, AVG, MIN, MAX
- GROUP BY, HAVING, and filtering aggregated results
2SQL Joins & Advanced Queries
- INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN
- Subqueries and common table expressions (CTEs)
- Window functions — ROW_NUMBER, RANK, LEAD, LAG
- Date functions and time-series queries
3Excel for Business Analysis
- Pivot tables — grouping, calculated fields, and slicers
- VLOOKUP, INDEX/MATCH, and XLOOKUP for data retrieval
- Conditional formatting and data validation rules
- Charts — bar, line, scatter, and combination charts
4Python for Data Analysis — Pandas
- Python basics — variables, lists, dictionaries, loops, functions
- Pandas DataFrames — loading CSV/Excel, selection, filtering
- Data cleaning — handling missing values, duplicates, type conversions
- Groupby operations and summary statistics
5Data Visualization with Python
- Matplotlib — bar charts, line charts, histograms, and subplots
- Seaborn — statistical plots, heatmaps, and box plots
- Choosing the right chart type for your data and audience
- Annotating and customizing plots for presentations
6Power BI Fundamentals
- Power BI Desktop — data import, transformations, and data model
- DAX basics — calculated columns, measures, and CALCULATE
- Visualizations — cards, tables, bar charts, maps, and slicers
- Filters, drill-through pages, and bookmarks
7Advanced Analytics & Business Metrics
- Cohort analysis and customer lifetime value calculation
- Churn analysis, retention curves, and funnel metrics
- A/B test analysis — statistical significance and practical significance
- Forecasting basics — moving averages and trend analysis
8Capstone Project & Interview Preparation
- End-to-end analytics project execution and presentation
- Data analyst interview question patterns — SQL, case studies, metrics
- Storytelling with data — structuring findings for stakeholders
- Portfolio presentation and resume optimization for analyst roles
Hands-On Labs Included
You build these yourself — guided exercises with real tools, not passive demos.
SQL Queries on E-Commerce Database
Docker Lab2 hours
SQL Joins & Window Functions
Docker Lab2 hours
Excel Business Report with Pivot Tables
Docker Lab1.5 hours
Python Data Cleaning with Pandas
Docker Lab2 hours
Power BI Dashboard — Sales Performance
Docker Lab2.5 hours
Who Is This For?
Freshers & Graduates
Just graduated or finishing your degree? This course gives you the practical skills and portfolio projects that campus placements and entry-level interviews demand.
Career Switchers
Moving from another domain into tech? The structured curriculum and real-world projects bridge the gap between theory and what employers actually look for.
Ideal If You Are:
- Fresh graduates looking for their first analytics role
- Business professionals in finance, marketing, or operations wanting data skills
- Career switchers with no programming background entering tech
- Excel power users who want to level up to SQL, Python, and Power BI
Prerequisites
- No programming experience required
- Basic computer literacy and comfort with spreadsheets
- A laptop with at least 8 GB RAM
- Willingness to practice SQL and Python exercises between sessions
Career Support Included
We don't just teach you — we help you land the job.
Mock Interviews
Practice with real-world interview scenarios. Get feedback on technical depth, communication, and problem-solving approach.
Resume Review
One-on-one review sessions to craft a resume that highlights your projects, skills, and achievements the right way.
Portfolio Coaching
Guidance on presenting your course projects as professional portfolio pieces that stand out to hiring managers.
LinkedIn Optimization
Tips and templates to optimize your LinkedIn profile so recruiters find you and reach out.
Learn from Industry Practitioners
Our instructors are working professionals who build production systems daily. They bring real-world experience, battle-tested patterns, and the kind of practical insight that textbooks can't teach.
Course Details
| Format | Live Online |
|---|---|
| Duration | 8 weeks |
| Schedule | 12 sessions |
| Batch Size | Max 15 students |
| Certificate | Yes, on completion |
| Lab Setup | Docker-based (runs on your laptop) |
| Price | Enquire for pricing |
Frequently Asked Questions
Will I get a job after completing this program?
Data analyst roles are in high demand across every industry. Our curriculum covers the exact skills hiring managers screen for — SQL, Python, Power BI, and business metrics. While we cannot guarantee placement, graduates with strong portfolio dashboards and SQL proficiency are competitive candidates.
Do I need experience with programming or SQL?
No. This is a beginner-friendly program. We teach SQL, Python, and Power BI from absolute fundamentals. If you can use Excel and are comfortable with basic math, you are ready.
Is this enough to become a data scientist?
This program prepares you for data analyst roles. If you want to become a data scientist, this is an excellent foundation — you can follow up with our Data Science & Machine Learning program after completing this course.
Do I need to install special software?
We use Docker for SQL environments, free Python tools (Jupyter), and Power BI Desktop (free). Setup is guided in the first session.
How many hours per week should I dedicate?
Plan for 3-4 hours of live sessions plus 3-4 hours of practice assignments per week. Consistent practice is more important than long study sessions.
What if I miss a live session?
All sessions are recorded and available on the student portal within 24 hours. The instructor and TAs are available on Slack for questions.
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Ready to Start Your Data Analytics Accelerator Journey?
Talk to us to learn about upcoming batches, pricing, and payment plans.