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Students After 12th
The programme is suitable for students who have completed 12th and want to enter technology, analytics or business-oriented roles without beginning with advanced programming.
Start right after school
Best After 12th 6-Month Data Analytics & Business Analysis Certificate Program in Mohali
Start with spreadsheets and basic programming, then progress toward SQL, Python, Power BI, Tableau, business analysis, cloud data platforms, machine learning and AI-assisted analytics. This six-month programme is designed to help students after 12th build practical projects and a portfolio for entry-level analytics and business-focused technology roles.
0113
01Where this starts
Course Overview
The six-month programme starts from the fundamentals and gradually moves toward professional analytics workflows.
During the first two months, you build a strong foundation in Excel, SQL, Python, statistics and data analysis. You learn how businesses store information, how analysts clean datasets and how reports are converted into useful decisions.
Month 3 focuses on Python for analytics, including NumPy, Pandas, exploratory data analysis, visualisation, APIs, web scraping and Streamlit.
Month 4 moves into Business Intelligence, where you work with Power BI, Power Query, data modelling, DAX and Tableau.
Month 5 introduces the business analyst side of technology. You learn requirement gathering, stakeholder analysis, BRD, FRD, SRS, user stories, acceptance criteria, Agile, Scrum, Jira, Confluence and BPMN. Modern data platforms including Microsoft Fabric, Snowflake and DuckDB are also introduced.
The final month brings together AI, machine learning, automation and portfolio development, followed by interview preparation and an end-to-end analytics capstone.
The result is a programme that covers both sides of modern analytics: technical data skills and business problem-solving skills.
Where it takes you
- Data Analyst
- Junior Data Analyst
- MIS Executive
- Reporting Analyst
- Business Analyst
- Junior Business Analyst
- BI Executive
- BI Analyst
- Data Reporting Executive
- Analytics Executive
- Operations Analyst
- Junior BI Developer
- Freelance Data Analyst
02Skills you collect
What You'll Learn
Every stage of the programme is connected to practical work so that students gradually build a portfolio instead of completing the course with only theoretical notes.
Business Dashboards
Build practical Sales, HR, Inventory and Finance dashboards using Excel and Power BI. Learn data modelling, KPIs, DAX and dashboard storytelling.
Professional SQL
Move beyond basic SELECT queries into joins, CTEs, subqueries, CASE statements, window functions, views and query optimisation.
Python Analytics
Use Python, NumPy and Pandas to clean, transform and analyse datasets. Create visualisations using Matplotlib, Seaborn and Plotly.
Business Analysis Documentation
Learn how analysts convert business conversations into structured requirements through BRD, FRD, SRS, user stories, acceptance criteria and process maps.
Modern Data Platforms
Understand the concepts behind data warehouses, data lakes and lakehouses while exploring Microsoft Fabric, Snowflake, DuckDB, dbt and Airflow.
AI & Machine Learning
Learn practical machine learning concepts and discover how generative AI tools can support SQL, coding, reporting, research and analytics workflows.
03The route
Course Curriculum
The syllabus is divided into six progressive modules. Each month combines concepts, labs, assignments and project work.
- Introduction to Data Analytics
- Understand what data analytics means and how organisations use data for decision-making. Learn the analytics lifecycle and the difference between descriptive, diagnostic, predictive and prescriptive analytics.
- Explore applications across retail, finance, healthcare, marketing and operations.
- Practical Work
- Set up Python and VS Code
- Install Anaconda and Git
- Configure MySQL and DBeaver
- Install Power BI and Tableau
- Create GitHub and LinkedIn profiles
- Introduction to ChatGPT, Microsoft Copilot, GitHub Copilot and Gemini
- Advanced Excel — build confidence with Excel as an analyst's first reporting tool.
- Data cleaning
- Tables and formatting
- Pivot tables
- Pivot charts
- XLOOKUP
- INDEX-MATCH
- IF functions
- Conditional formatting
- Power Query fundamentals
- Dashboard design
- Lab: Sales, HR and Inventory dashboards.
- SQL Fundamentals — learn how relational databases store business information.
- Databases and tables
- Primary and foreign keys
- SELECT
- WHERE
- GROUP BY
- HAVING
- ORDER BY
- Aggregate functions
- Introduction to joins
- Lab: Retail and HR database analysis.
- Python Fundamentals — start programming from the basics.
- Variables
- Data types
- Operators
- Conditions
- Loops
- Functions
- File handling
- Exception handling
- OOP fundamentals
- Lab: Calculator, employee record processor and CSV reader.
- Mini Project — Retail Sales Performance Analysis: combine Excel, SQL and Python to analyse sales information and prepare a business-oriented summary.
Learn Through Projects, Not Just Lectures
A strong analytics portfolio should demonstrate what you can actually do. Throughout the programme, students can work on business dashboards, SQL reporting, Python analysis, data visualisation, business requirements, BPMN process mapping, data architecture concepts, AI-assisted analytics and end-to-end capstone development.
Outcome
The capstone runs the whole chain in one project — requirement gathering, SQL, Python, data visualisation, Power BI, business analysis, AI-assisted reporting and an executive presentation.
04Your toolkit
Tools You Will Work With
The programme introduces a broad analytics toolchain covering spreadsheets, databases, programming, BI, business analysis, cloud data and AI.
Microsoft ExcelPower QueryPythonNumPyPandasMatplotlibSeabornPlotlyJupyterVS CodeMySQLSQLDBeaverDuckDBPower BIPower BI ServiceTableauJiraMicrosoft ExcelPower QueryPythonNumPyPandasMatplotlibSeabornPlotlyJupyterVS CodeMySQLSQLDBeaverDuckDBPower BIPower BI ServiceTableauJiraMicrosoft ExcelPower QueryPythonNumPyPandasMatplotlibSeabornPlotlyJupyterVS CodeMySQLSQLDBeaverDuckDBPower BIPower BI ServiceTableauJira
ConfluenceLucidchartFigmaBPMNMicrosoft FabricSnowflakedbtApache AirflowREST APIsPostmanChatGPTMicrosoft CopilotGitHub CopilotGoogle GeminiClaudeOpenAI API conceptsLangChainStreamlitConfluenceLucidchartFigmaBPMNMicrosoft FabricSnowflakedbtApache AirflowREST APIsPostmanChatGPTMicrosoft CopilotGitHub CopilotGoogle GeminiClaudeOpenAI API conceptsLangChainStreamlitConfluenceLucidchartFigmaBPMNMicrosoft FabricSnowflakedbtApache AirflowREST APIsPostmanChatGPTMicrosoft CopilotGitHub CopilotGoogle GeminiClaudeOpenAI API conceptsLangChainStreamlit
- Microsoft Excel
- Analytics & programming — cleaning, pivots and the first dashboards.
- Power Query
- Analytics & programming — repeatable data cleaning and shaping.
- Python
- Analytics & programming — the language behind months three and six.
- NumPy
- Analytics & programming — arrays, indexing and numeric work.
- Pandas
- Analytics & programming — DataFrames, GroupBy, merges and feature engineering.
- Matplotlib
- Analytics & programming — the base plotting library.
- Seaborn
- Analytics & programming — statistical charts for exploratory analysis.
- Plotly
- Analytics & programming — interactive visualisation.
- Jupyter
- Analytics & programming — notebooks for analysis and labs.
- VS Code
- Analytics & programming — the editor set up in month one.
- MySQL
- Databases & SQL — the relational database behind the reporting labs.
- SQL
- Databases & SQL — joins, CTEs, window functions and views.
- DBeaver
- Databases & SQL — the client you query and browse from.
- DuckDB
- Databases & SQL — analytical queries straight over local files.
- Power BI
- Business intelligence — data models, DAX and KPI dashboards.
- Power BI Service
- Business intelligence — publishing and sharing reports.
- Tableau
- Business intelligence — charts, maps, dashboards and stories.
- Jira
- Business analysis — sprints, issues and project workflow.
- Confluence
- Business analysis — where the requirements are documented.
- Lucidchart
- Business analysis — process and flow diagrams.
- Figma
- Business analysis — basic screens and wireframes.
- BPMN
- Business analysis — the notation behind the process maps.
- Microsoft Fabric
- Modern data platforms — the lakehouse-era analytics stack.
- Snowflake
- Modern data platforms — the cloud data warehouse.
- dbt
- Modern data platforms — transformations inside the ELT pipeline.
- Apache Airflow
- Modern data platforms — scheduling and orchestration.
- REST APIs
- Modern data platforms — where external data comes from.
- Postman
- Modern data platforms — testing and inspecting those APIs.
- ChatGPT
- AI & development — analysis, explanation and drafting support.
- Microsoft Copilot
- AI & development — assistance inside the Microsoft stack.
- GitHub Copilot
- AI & development — code completion for SQL and Python.
- Google Gemini
- AI & development — a second general assistant.
- Claude
- AI & development — long-document reporting and research work.
- OpenAI API concepts
- AI & development — calling models from your own code.
- LangChain
- AI & development — chaining models, tools and retrieval.
- Streamlit
- AI & development — shipping an analysis as an interactive app.
05Is this you?
Who Can Join This Course?
02
Commerce & Management Students
Students from B.Com, BBA and related backgrounds can combine their business understanding with Excel, SQL, Power BI and business analysis skills.
03
BCA, B.Sc & Technical Students
Students pursuing technical degrees can use the programme to strengthen their practical analytics, BI and business-analysis capabilities.
04
Students Preparing for Analyst Roles
If your target is an entry-level Data Analyst, MIS, Reporting or Business Analyst role, the curriculum provides practice across the tools commonly used in these workflows.
05
Career Switchers
Working professionals can use the structured learning path to move from routine reporting or non-technical work toward analytics-focused responsibilities.
06
Self-Learners
If you have learned individual tools through online tutorials but struggle to connect them into complete projects, the project-based structure can help create a more organised portfolio.
06Why this one
Why This Programme Is Worth Considering
01
Practical Learning
The programme moves from concepts to labs and projects so that you can apply each major skill instead of only reading about it.
02
Strong Excel & SQL Foundation
Excel, Power Query and SQL are developed beyond beginner-level reporting and include advanced querying and data preparation.
03
Python for Real Analysis
Python is introduced progressively and then applied to cleaning, EDA, APIs, visualisation and interactive applications.
04
Power BI & Tableau
Learn both major visualisation platforms while understanding data modelling, KPIs, DAX and dashboard storytelling.
05
Business Analysis Included
Requirement gathering, BRD, FRD, SRS, Agile, Scrum, Jira and BPMN make the programme broader than a purely technical analytics course.
06
Modern Data Concepts
Explore cloud data platforms, warehouse/lakehouse architecture, ELT, dbt and orchestration concepts.
07
AI & Machine Learning
Understand how machine learning and generative AI can support modern analytics workflows while maintaining the importance of human validation and business context.
08
Portfolio & Career Preparation
Build projects, organise your GitHub portfolio, improve your resume and practise technical and HR interviews.
07Why now
Build Analytics Skills for a Data-Driven Workplace
Businesses increasingly depend on dashboards, reports and data-backed decisions. Learning only one tool is often not enough; analysts need to understand where the data comes from, how it should be cleaned, how it should be presented and what business decision it supports.
This programme brings those stages together in one structured six-month learning path.
What the six months include
- Six months of structured analytics trainingSix modules, one per month, fundamentals through to career readiness.
- Monthly practical projectsA mini project closes every month, from month one onward.
- Excel, SQL and Python foundationsMonths 1 to 3 — dashboards, advanced querying, NumPy and Pandas.
- Power BI and TableauMonth 4 — data modelling, DAX, KPI cards, dashboards and stories.
- Business analysis documentationMonth 5 — BRD, FRD, SRS, user stories and acceptance criteria.
- Modern data platform conceptsMonth 5 — Fabric, Snowflake, DuckDB, dbt and Airflow.
- AI and machine learningMonth 6 — regression, classification, clustering and generative AI.
- Final portfolio projectMonth 6 — the end-to-end business analytics capstone.
- Resume and interview preparationMonth 6 — ATS-friendly resume, mock interviews and portfolio review.
Talk to a Course Advisor
Ten minutes with the techcadd team settles eligibility, session timings, fees and where this leads — before you commit six months to it.
08Certification
Complete the Data Analytics Certificate Program
Students who complete the programme can receive course-completion documentation according to the current techcadd programme terms. The focus is not only on completing classes but also on demonstrating your learning through assignments, practical work and projects.
Course Completion CertificateDocumentation for successful completion of the training programme, subject to current techcadd requirements.
Project DocumentationProject-based work that can be organised as part of your professional portfolio.
Analytics PortfolioA collection of dashboards, SQL work, Python analysis, business documentation and the final capstone.
Career SupportResume preparation, portfolio guidance and interview practice as offered under the current programme.
Capstone Defense
Fullscreen
Project Completion Certificate
ISO 9001:2015 Accredited
Fullscreen
Course Completion Certificate
Two documents on completion — the course certificate, and a separate certificate for the capstone you build and defend. Click any card to inspect in full screen.
09Where it leads
Where This Course Can Take You
The programme can prepare you for several entry-level and junior career paths, depending on your skills, portfolio, interview performance and employer requirements.
Potential Roles
Clean, query and analyse business datasets, then report what they show.
10What you build
Hands-On Projects You Will Build
01
Retail Sales Performance Analysis
Clean and analyse a retail dataset using Excel, SQL and Python, then prepare a concise business report. Month 1 · Excel · SQL · Python
02
Enterprise Sales Intelligence Dashboard
Use advanced SQL, Power Query and statistical analysis to create an executive sales reporting system. Month 2 · SQL · Excel · Power Query
03
Customer Insights Analytics System
Work with APIs and external data, clean the information with Pandas and create interactive visualisations using Plotly and Streamlit. Month 3 · Python · Pandas · Streamlit
04
Executive Business Intelligence Dashboard
Create a structured Power BI data model with DAX measures and executive KPIs, then develop a complementary Tableau dashboard. Month 4 · Power BI · Tableau
05
Business Process & Data Platform Design
Prepare business requirements, user stories, BPMN diagrams and a conceptual modern data architecture. Month 5 · BRD · FRD · BPMN · Fabric
06
Enterprise Analytics Capstone
Bring together requirements, SQL, Python, BI, business analysis and AI-assisted reporting in one end-to-end portfolio project. Month 6 · Capstone
11How it works
Learn It. Build It. Present It.
The learning cycle is simple:
This approach helps turn a completed assignment into something you can actually discuss during an interview.
Understand
Start by understanding the business question, available data and expected outcome.
Retail Sales Performance AnalysisBuild
Apply the relevant tools to clean, analyse, model and visualise the information.
Enterprise Sales Intelligence DashboardPresent
Explain what you discovered, why you used a particular approach and what action the business could consider.
Customer Insights Analytics System12Why techcadd
Why Students Can Choose techcadd
A curriculum that builds in order, a project at every stage, and the business-analysis half most analytics courses leave out.
01
Structured Learning Path
The curriculum progresses from fundamentals to advanced topics rather than expecting beginners to understand everything immediately.
02
Practical Assignments
Regular labs and projects give students opportunities to apply concepts throughout the programme.
03
Analytics + Business Analysis
Students learn technical analytics as well as the documentation and requirement skills used in business-facing roles.
04
Project-Based Portfolio
Six major project stages provide multiple opportunities to create work that can be presented in a portfolio.
05
Modern Technology Exposure
The programme introduces cloud data platforms, modern data engineering concepts, AI and machine learning alongside established analytics tools.
06
Interview Preparation
Technical questions, business scenarios, resume development, portfolio presentation and mock interviews are included as part of career preparation.
13Who has walked it
Students who started where you are
Alumni of this route, on what changed once they were sitting in interviews.
4.8
373 reviews
584%
410%
34%
22%
10%
AutoCAD and SolidWorks were taught with actual production drawings, not textbook exercises. My employer noticed that my drawing sets followed proper standards from day one.
I joined the 6-month MERN track straight after B.Tech with almost no practical experience. The live project work is what changed things — I had real code to talk about in interviews instead of just a syllabus.
The trainers actually work in the field, so every session had context from real projects. The Power BI and SQL modules were exactly what my interview rounds tested.
The Generative AI course was current in a way online tutorials are not. Building a full RAG pipeline and deploying it gave me something genuinely impressive for my portfolio.
14Before you go
Frequently Asked Questions
Still unsure? A ten-minute call with a counsellor usually settles it faster than any brochure.
By the end of the programme, you should be able to work through a typical analytics assignment from raw information to business recommendation. You will practise cleaning and analysing datasets, writing SQL queries, using Excel and Power Query, analysing data with Python and Pandas, creating visualisations, building Power BI dashboards, developing Tableau stories, understanding DAX and data models, gathering business requirements, writing BRD, FRD and SRS documents, creating BPMN process maps, working with Agile concepts, using Jira for project workflows, understanding modern data architectures, applying basic machine learning, using AI tools as analytics assistants, presenting insights to stakeholders and building a professional analytics portfolio.
15Final stage
Ask About the Data Analytics Certificate Program in Mohali
Have questions about the syllabus, fees, session timings, eligibility or career pathway?
Speak with a course counsellor to understand whether this six-month programme matches your academic background and career goals.
Location: Mohali, Punjab. Counselling hours: Monday to Saturday, 9:00 AM to 7:00 PM.
+91 98881 22442Call the admissions desk+91 98881 22442WhatsApp for a quick replyinfo@techcadd.comEmail us your questions
Your details are used only to contact you about this enquiry — never sold, never added to a marketing list.
Other routes
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Still deciding
Not Sure If Data Analytics Is the Right Choice?
If you are planning your next step after 12th and are interested in data, dashboards, technology and business decision-making, a counselling session can help you compare the available learning paths.
Book a free demo or speak with the Mohali team to understand the current curriculum, session schedule and programme requirements.
Get Started Today
- 6 months, 12th pass and above, any stream
- Excel, SQL, Python and business statistics from the fundamentals
- Power BI, Power Query, DAX and Tableau
- Business analysis — BRD, FRD, SRS, Agile, Scrum, Jira and BPMN
- Microsoft Fabric, Snowflake, DuckDB, dbt and Airflow
- Machine learning, generative AI and AI-assisted reporting
- 6 project stages and an end-to-end analytics capstone