Flagship project
Sales Analytics Dashboard
Build an interactive dashboard that tracks sales performance, top products, and regional trends.
- Power BI
- SQL
- Data Visualisation
Data Analytics MasterclassHigh-Growth Skill
Complete Data Analytics Masterclass in Amritsar – Zero to Job Ready with Real Projects & Placement Support
Complete Data Analytics Masterclass Course course in AmritsarJob-oriented data analytics training built on real industry scenarios — small batches, daily hands-on labs and 100% placement assistance.
3 / 6 MonthsBeginnerClassroom & live online
3 / 6 Months
Duration
Weekday/Weekend
Mode
12th Pass/Any Grad
Eligibility
10-12 Students
Batch Size
Admissions open
Complete Data Analytics Masterclass Course · 3 / 6 Months
Batch timings
- Morning
- Evening
- Weekend
- Live online
About the programme
Course overview
Course overviewtechcadd's Complete Data Analytics Masterclass in Amritsar is a practical, project-first introduction to data analytics for beginners and career switchers.
It opens with analytics fundamentals, Excel, and data visualisation principles, then moves into SQL, Python for data analysis, Power BI, statistics, and business reporting on real datasets.
You finish with a documented data analytics portfolio, a capstone project, CV preparation and interview coaching.
Every business in Amritsar — from retail shops near Hall Bazaar to IT companies on Airport Road, from local startups to D2C brands scaling across India — is trying to figure out how to use data. The problem isn’t access to the data; it’s knowing how to turn it into decisions. Spreadsheets are everywhere, but they don’t tell you why sales dropped last quarter, which customer segment is most profitable, or where your marketing budget is being wasted. The real skill isn’t just collecting data — it’s building systems that clean, analyse, visualise, and communicate it. That’s Data Analytics. It’s the ability to take raw, messy data and turn it into dashboards, insights, and business decisions that leaders actually act on. Companies are desperate for people who can build these bridges between their data and their decision-making, saving thousands of hours and unlocking new levels of productivity.
techcadd's Complete Data Analytics Masterclass in Amritsar is built on the projects you actually see in job descriptions and client briefs — data cleaning, SQL querying, dashboard building, statistical analysis, and business reporting — not abstract theory. You work with real datasets and real business questions 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 analytics problems.
Placement assistanceLive analytics labsInternship certificate
- Duration
- 3 / 6 Months
- Level
- Beginner
- Mode
- Classroom & live online
- Batches
- Morning, evening & weekend
Module by module
The curriculum, module by module
Module by module curriculumThe Complete Data Analytics Masterclass 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
Analytics Fundamentals & Data Visualisation Principles
The foundational knowledge every data analyst assumes you already know — how to clean data and how to present it clearly.
Topics covered
- Analytics basics
- Excel
- data cleaning
- data visualisation
- chart selection
- dashboard design
- storytelling with data
- ethical considerations
Tools in this module
Microsoft ExcelGoogle SheetsTableau PublicPower BIGoogle Data StudioYou finish withA documented visualisation portfolio with foundational dashboard exercises
- Module 02 of 06
SQL, Python & Data Analysis
Core data analytics — querying databases and analysing data with Python.
Topics covered
- SQL queries
- joins
- aggregations
- Python for data analysis
- Pandas
- NumPy
- data wrangling
- exploratory data analysis
Tools in this module
MySQLPostgreSQLPythonPandasNumPyJupyterGoogle ColabYou finish withA data analysis project that answers business questions from a real dataset
- Module 03 of 06
Capstone Project, Career & Interview Readiness
A capstone project combining data cleaning, analysis, dashboard building, and business insights, plus career readiness for data analyst roles.
Topics covered
- End-to-end data analytics project
- problem framing
- business solution design
- portfolio development
- resume
- LinkedIn profile
- interview readiness
- data analytics certification exam preparation
Tools in this module
PythonSQLPower BIGitHubPortfolioResumeLinkedInMock interviewsYou finish withA complete capstone project with documentation, and an interview-ready data analytics portfolio and resume
- Module 04 of 06
Advanced Analytics & Business Intelligence
Advanced analytics and business intelligence — creating predictive models and executive dashboards that drive business decisions.
Topics covered
- Advanced statistics
- predictive analytics
- Power BI
- DAX
- data modelling
- KPI design
- business intelligence
- evaluation metrics
Tools in this module
Power BITableauDAXSQLPythonScikit-learnYou finish withA business intelligence dashboard that automates a multi-step reporting process using predictive analytics
- Module 05 of 06
Python for Data Science & Machine Learning Basics
Machine learning and optimization — applying predictive models to specialised business tasks and improving analytics performance.
Topics covered
- Machine learning basics
- regression
- classification
- clustering
- model evaluation
- feature engineering
- Scikit-learn
Tools in this module
Scikit-learnMatplotlibSeabornHugging FaceGoogle ColabJupyterYou finish withA report on building a machine learning model for a specific business domain
- Module 06 of 06
Advanced Capstone, Career & Interview Readiness
An advanced capstone project combining data analytics, business intelligence, predictive analytics, and business impact, plus career readiness for senior data analyst roles.
Topics covered
- Full data analytics project lifecycle
- problem framing
- data strategy
- system 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
Analyse customer data to identify high-value segments and churn risks using Python and statistics.
- Python
- Pandas
- Statistics
Predictive Sales Forecasting Model
Build a machine learning model to forecast future sales and evaluate its performance.
- Machine Learning
- Scikit-learn
- Forecasting
Expert Capstone Project
Complete an end-to-end data analytics project with deployment, monitoring, and business impact.
- Multi-Domain
- Portfolio
- Deployment
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 analytics teams use it, with the workflow and standards a data analyst expects.
Sales Analytics Dashboard
- 02
Real datasets and projects
Every module runs on real 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 project reviewed weekly by a mentor who still works on live analytics problems.
Predictive Sales Forecasting Model
- 04
Real projects and scenarios from the start
Every dashboard and analysis is built on real-world data briefs and measured through accuracy, efficiency, and business impact, the way analytics 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 projects you can show and data analytics workflows 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 Complete Data Analytics Masterclass 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 analytics problems
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 Complete Data Analytics Masterclass Course course
Who can join the Complete Data Analytics Masterclass 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 Complete Data Analytics Masterclass 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.
19tools covered
Spreadsheet software
- Microsoft Excel
- Google Sheets
Query language
- SQL
Relational database
- MySQL
- PostgreSQL
Programming language
- Python
Data analysis library
- Pandas
Numerical computing library
- NumPy
Data visualisation library
- Matplotlib
Statistical data visualisation
- Seaborn
Machine learning library
- Scikit-learn
Business intelligence tool
- Power BI
Data visualisation tool
- Tableau
- Google Data Studio
Notebook environment
- Jupyter
Cloud notebooks
- Google Colab
Version control
- Git
Code hosting
- GitHub
Code editor
- VS Code
Certification
Get certified in Complete Data Analytics Masterclass Course
Get certified in Complete Data Analytics Masterclass 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 analytics is the new baselineEmployers increasingly assume analytical knowledge will extend to data communication and automation.
- Automation and AI are the new layersTeams expect data analysts to integrate AI agents, automation, and privacy-first analytics practices, not just write SQL.
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 | Usually limited to basic Excel |
| Batch size | 10–12 students per batch | Often 25–40 students per batch |
| Data Analytics & BI | Live integration, real projects | Rarely covered |
| Advanced topics | Machine learning, predictive analytics, automation | Often only theory |
| Automation & Scripts | Data pipelines, Zapier, Make | 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 | Often only a completion certificate |
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.
