Flagship project
Sales Dashboard for Retail Business
Build an interactive sales dashboard that tracks revenue, profit margins, top products, and regional performance using Excel, SQL, and Power BI.
- Dashboard
- Power BI
- SQL
Data Analytics for Beginners CourseHigh-Demad
Complete Data Analytics for Beginners Course in Amritsar – Zero to Job Ready with Real Projects & Placement Support
Data Analytics for Beginners Course course in AmritsarJob-oriented data analytics training built on real business data — small batches, daily hands-on labs and 100% placement assistance.
3 / 6 MonthsBeginnerHybrid
3 / 6 Months
Duration
Weekday/Weekend
Mode
12th Pass/Any Grad
Eligibility
10-12 Students
Batch Size
Admissions open
Data Analytics for Beginners Course · 3 / 6 Months
Batch timings
- Morning
- Evening
- Weekend
- Live online
About the programme
Course overview
Course overviewtechcadd's Complete Data Analytics for Beginners Course in Amritsar is a practical, project-first introduction to Data Analytics for beginners and career switchers.
It opens with Excel fundamentals, data cleaning, SQL basics, descriptive statistics, and data visualization, then moves into Python for data analysis, advanced SQL, dashboard development, business intelligence, predictive analytics, and storytelling with data on real datasets.
You finish with a documented data analytics portfolio, a capstone project, CV preparation and interview coaching.
Every business in Amritsar — from traditional manufacturers near Focal Point to cutting-edge IT firms on Airport Road, from local startups to healthcare providers scaling across Punjab — is drowning in data. Sales records, customer databases, website analytics, financial transactions, inventory logs, marketing metrics, and operational reports pile up faster than any team can analyze them. The problem isn't collecting data; it's making sense of it. Data Analytics is how you turn raw, messy, scattered numbers into actionable intelligence: dashboards that reveal what's actually happening in your business, trend analysis that spots opportunities before competitors do, customer segmentation that tells you who your best customers really are, sales forecasting that predicts demand, and performance metrics that guide smart decisions. Companies need professionals who can clean and transform data, build interactive dashboards, write SQL queries that answer business questions, perform statistical analysis to validate hypotheses, and communicate insights that drive strategy. The real skill isn't memorising formulas — it's building data systems that work on real, messy, business data.
techcadd's Data Analytics for Beginners Course in Amritsar is built on the tools and platforms you actually see in job descriptions and business analyst briefs — Excel, SQL, Python, Power BI, Tableau, Google Analytics, and statistics — not abstract theory. You work with real business datasets, real dashboard projects, and real analytics pipelines from the very first module and finish with a documented data analytics portfolio, not just a certificate. The programme runs in a 3-month foundation track, with an optional 6-month extended track for deeper mastery. Batches are capped at 10–12 students, and every project you build is reviewed weekly by mentors who still work on live data analytics systems and business intelligence pipelines.
Placement assistanceLive analytics labsInternship certificate
- Duration
- 3 / 6 Months
- Level
- Beginner
- Mode
- Hybrid
- Batches
- Morning, evening & weekend
Module by module
The curriculum, module by module
Module by module curriculumThe Complete Data Analytics for Beginners Course is a nested ladder — the longer track includes every module from the shorter track and adds more depth. No module is repeated; you continue building on the skills you have already learned.
- Module 01 of 06
Excel, Data Cleaning & SQL Fundamentals
The foundational knowledge every Data Analyst assumes you already know — how to clean, organize, and query raw business data.
Topics covered
- Excel formulas
- pivot tables
- data cleaning
- data transformation
- SQL basics
- SELECT queries
- filtering
- sorting
- joins
- data normalization
Tools in this module
Microsoft ExcelGoogle SheetsMySQLPostgreSQLSQLiteJupyterYou finish withA documented data cleaning and SQL querying project on a real business dataset
- Module 02 of 06
Descriptive Statistics, Data Visualization & Dashboard Basics
Core data analytics modeling — building dashboards and visualizations that reveal business insights from raw data.
Topics covered
- Descriptive statistics
- mean
- median
- mode
- standard deviation
- correlation
- data visualization
- charts
- graphs
- dashboard design
- KPI tracking
- business reporting
Tools in this module
ExcelGoogle SheetsPower BITableauMatplotlibSeabornGoogle AnalyticsYou finish withAn end-to-end dashboard and data visualization project deployed on a real dataset
- Module 03 of 06
Capstone Project, Career & Interview Readiness
A capstone project combining data cleaning, SQL querying, dashboard development, and business insights, plus career readiness for data analytics roles.
Topics covered
- End-to-end data analytics project
- problem framing
- analytics system design
- portfolio development
- resume
- LinkedIn profile
- interview readiness
- data analytics certification exam preparation
Tools in this module
ExcelSQLPower BITableauGitHubPortfolioResumeLinkedInMock interviewsYou finish withA complete capstone project with documentation, and an interview-ready data analytics portfolio and resume
- Module 04 of 06
Python for Data Analysis, Advanced SQL & Statistical Modeling
Advanced data analysis — using Python and advanced SQL to perform statistical modeling and predictive analytics on real business data.
Topics covered
- Python programming
- Pandas
- NumPy
- data manipulation
- advanced SQL
- subqueries
- window functions
- stored procedures
- hypothesis testing
- regression analysis
- correlation analysis
- predictive modeling
Tools in this module
PythonPandasNumPyMatplotlibSeabornScikit-learnMySQLPostgreSQLJupyterGoogle ColabYou finish withA statistical modeling and predictive analytics project for a real business dataset
- Module 05 of 06
Power BI, Tableau, Business Intelligence & Data Storytelling
Business intelligence and dashboard development — building interactive dashboards and automated reports that drive business decisions.
Topics covered
- Power BI
- Tableau
- advanced dashboard design
- business intelligence
- data storytelling
- KPI development
- report automation
- data governance
- analytics deployment
Tools in this module
Power BITableauExcelPythonSQLGoogle AnalyticsLooker StudioFastAPIStreamlitYou finish withA Power BI and Tableau dashboard portfolio with documentation
- Module 06 of 06
Advanced Capstone, Career & Interview Readiness
An advanced capstone project combining data cleaning, SQL, Python, statistics, dashboards, and business impact, plus career readiness for senior data analytics roles.
Topics covered
- Full data analytics project lifecycle
- problem framing
- analytics strategy
- dashboard deployment
- portfolio development
- resume
- LinkedIn profile
- interview readiness
- data analytics certification exam preparation
Tools in this module
GitHubPortfolioResumeLinkedInMock interviewsCase studiesYou finish withA complete advanced capstone project with documentation, and an interview-ready data analytics portfolio and resume
What you build
Projects that answer the interview question for you
Portfolio projectsEach project is reviewed individually, and the review notes go into your portfolio documentation.
Customer Segmentation Analysis
Create a customer segmentation system that groups customers by purchase behavior, demographics, and lifetime value using Python, Pandas, and Scikit-learn.
- Segmentation
- Python
- Scikit-learn
Marketing Performance Analytics
Build a marketing analytics dashboard using Google Analytics, Tableau, and SQL that tracks campaign ROI, conversion rates, and customer acquisition costs.
- Marketing Analytics
- Tableau
- Google Analytics
Expert Capstone Project
Complete an end-to-end data analytics project with data cleaning, SQL querying, statistical analysis, dashboard development, and a business recommendation plan.
- Multi-Domain
- Portfolio
- Data Strategy
The working loop
Learn it. Build it. Make it yours.
Learn it. Build it. Make it yours.Every project moves through the same loop: understand the brief, build it with guidance, then explain the decisions behind your work. The certificate is the receipt — the portfolio is the point.
- 01
Industry-focused curriculum
You learn it the way professional data analysts use it, with the workflow and standards a Data Analyst expects.
Sales Dashboard for Retail Business
- 02
Real datasets and projects
Every module runs on real business datasets with real business questions and real outcomes, not a slide or a screenshot.
Customer Segmentation Analysis
- 03
Mentor-reviewed deliverables
Each module ends with a working analytics project reviewed weekly by a mentor who still works on live data analytics problems.
Marketing Performance Analytics
- 04
Real projects and scenarios from the start
Every dashboard and analysis project is built on real-world business briefs and measured through accuracy, insight quality, and business impact, the way data teams work.
Expert Capstone Project
The honest pitch
Your months should build more than a certificate.
Your months should build more than a certificate.A course is worth the time you give it only if you finish with real data analytics projects you can show and business insights you can defend.
Project completion certificate
Issued for the project you build and defend
Course completion certificate
Carries a certificate ID and a scan-to-verify code
Why choose Data Analytics for Beginners Course
Why students choose techcadd
Why students choose techcaddWhat makes this course at techcadd different from a typical alternative is that every module is built on a real data analytics project and documented to professional standards, so you finish with an end-to-end data analytics portfolio rather than disconnected certificates.
- 01
Mentors who still work on live data analytics systems
Not full-time lecturers — trainers who are still doing the job they teach.
- 02
One project, extended through every module
You start the project in Module 01, extend it through every module, and complete the capstone by Module 03 or 06.
- 03
Small batch sizes
10–12 students per batch ensures every student gets personalised feedback on every deliverable.
- 04
Nested, no-repeat curriculum
Longer programs include everything from shorter tracks and add more depth — you never repeat a module.
- 05
Documented internship experience
Every student receives a documented internship certificate alongside their course certificate.
- 06
Placement support
Resume and LinkedIn preparation, interview coaching, and active placement assistance for graduates.
Eligibility
Who can join the Data Analytics for Beginners Course course
Who can join the Data Analytics for Beginners Course courseThis course works for a specific starting point — here's who gets the most out of it.
- Educational backgroundNo specific degree or stream required — school leavers, graduates and career switchers all qualify.
- Prior experienceNone required. The programme opens at beginner level and builds from there across 3 / 6 months.
- AgeNo upper age limit. What matters is being able to commit to the full course rather than dropping off midway.
- EquipmentA laptop or desktop with a stable internet connection for classroom or live-online batches.
- Time commitmentAble to attend regularly across 3 / 6 months, in a morning, evening or weekend batch.
Where it leads
The roles this portfolio opens
Job titles vary by company, but the underlying expectations do not. Each destination below maps to work you will have already done during the programme.
Tools you will actually use
The working stack for Data Analytics for Beginners Course
Tools and technologies coveredEvery tool below is installed, configured and used by you during the course — not demonstrated on a slide. You leave able to set up your own environment from scratch.
20tools covered
Spreadsheet software
- Excel
Cloud spreadsheet
- Google Sheets
Database query language
- SQL
Relational database
- MySQL
- PostgreSQL
Embedded database
- SQLite
Programming language
- Python
Data manipulation
- Pandas
Numerical computing
- NumPy
Data visualization
- Matplotlib
- Tableau
Statistical visualization
- Seaborn
Interactive visualization
- Plotly
Machine learning library
- Scikit-learn
Business intelligence
- Power BI
Web analytics
- Google Analytics
Dashboard & reporting
- Looker Studio
Model serving API
- FastAPI
App development
- Streamlit
Notebook environment
- Jupyter
Cloud notebooks
- Google Colab
Version control
- Git
Code hosting
- GitHub
Code editor
- VS Code
Certification
Get certified in Data Analytics for Beginners Course
Get certified in Data Analytics for Beginners CourseIssued on completion against the modules you finished and the projects you submitted — plus an internship letter where the industrial training track applies. Shareable to LinkedIn, and verifiable by an employer who calls the Amritsar desk.
- Module-wise assessment, not attendance-based
- Project submissions logged against your certificate
- Internship letter on the industrial training track
- Verifiable directly with the campus office
Future scope
Where this takes you over the next five years
Where this takes you over the next five yearsThe skill does not stand still, and neither does what it is worth.
- Data literacy is the new baselineEmployers increasingly assume business knowledge will extend to data analysis, dashboards, and statistical thinking.
- Business intelligence and predictive analytics are the new layersTeams expect data analysts to integrate Power BI, Tableau, Python, and predictive modeling, not just build basic reports.
The objective is practical knowledge rather than memorised concepts.
Due diligence
How techcadd compares
How techcadd comparesWhat actually differs between this course at techcadd and a typical alternative.
| What you should ask | techcadd Amritsar | Other institutes |
|---|---|---|
| Live project work | Every module, from week one | Varies, often only at the end |
| Learning format | One project extended through every module | Topics demonstrated separately, rarely combined |
| Tools used | Excel, SQL, Python, Power BI, Tableau | Usually limited to basic Excel and theory |
| Batch size | 10–12 students per batch | Often 25–40 students per batch |
| Analytics & Deployment | Live integration, real dashboards | Rarely covered |
| Advanced topics | Python, Predictive Analytics, Business Intelligence | Often only theory |
| Automation & Scripts | Automated reporting, dashboard alerts | Rarely covered |
| Portfolio | 6 documented project deliverables | Often just assignments, not portfolio-ready work |
| Certificate | Completion certificate + documented internship | Only a completion certificate |
| Placement support | Resume, LinkedIn, interview coaching, active placement | Generic referrals, no dedicated coaching |
Every comparison here is about substance, not marketing language.
Before you enrol
Questions we get asked at the admissions desk
Frequently asked questionsIf something here is not covered, the Amritsar desk will answer it directly — no call-back queue.
No. The programme opens at beginner level and assumes no background beyond comfort with a computer. Students who already have some exposure move through the early modules faster and spend the saved time on project work.
