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PROFESSIONAL DATA ANALYTICS & AI PROGRAM IN JAIPUR

Data Analytics Course in Jaipur with AI, Power BI, SQL & Python

Learn to turn raw data into clear dashboards, business insights and confident recommendations through guided practice, six portfolio projects and a maximum-five-learner batch.

Maximum 5 learners 6 documented projects Responsible AI practice

Final trainer, schedule, duration, delivery mode, fee, teaching language and certificate criteria are confirmed during counselling. No job, salary or placement outcome is guaranteed.

Decision Intelligence Studio Data quality checked
BUSINESS PERFORMANCEExecutive decision dashboard
Refresh complete
Revenue₹12.8L+14.2%
Conversion4.86%+0.72
Return rate7.4%Needs review
Trend and forecastJAN — JUN
ExcelSQLPower BIDecision
AI-assisted, human-validated Recommendation ready
Excel & SheetsCleaning and reporting
SQLBusiness queries
Power BIModels and dashboards
PythonPandas and visualisation
6 ProjectsPortfolio evidence
Why analytics now

Move from rows of data to decisions people can use

Organisations collect information across sales, marketing, operations and customers. Analysts make that information reliable, interpretable and useful.

01

What changed?
Compare actual performance with a useful baseline.

02

Why did it change?
Segment, investigate and test reasonable explanations.

03

What needs attention?
Surface risk, quality issues and meaningful exceptions.

04

What should happen next?
Translate findings into an accountable recommendation.

The analyst workflow

What does a data analyst actually do?

A data analyst defines a question, gathers approved information, cleans and connects it, finds patterns, builds reporting and explains the next action—with limitations visible.

Business-first, not software-first

The programme teaches tools as part of a responsible decision workflow.

ANALYST RESPONSIBILITY

Prepare

Clean, reshape and connect reliable data.

ANALYST RESPONSIBILITY

Analyse

Compare patterns, KPIs and segments.

ANALYST RESPONSIBILITY

Explain

Build a dashboard and recommend action.

Learning outcomes

Build the complete entry-level analyst stack

Each capability connects to practical work and visible evidence rather than isolated software demonstrations.

Prepare reliable data

Clean, transform and connect data from spreadsheets, databases and approved sources.

Query with SQL

Filter, join, aggregate and analyse business data with practical SQL workflows.

Build decision dashboards

Create useful Excel and Power BI reporting with DAX, filters and strong visual hierarchy.

Analyse with Python

Use Pandas and visualisation libraries for repeatable cleaning and exploration.

Work responsibly with AI

Use AI to assist formulas, code and explanation while validating outputs and protecting data.

Tell the data story

Present findings, uncertainty and recommendations for a real stakeholder decision.

Document a portfolio

Show the question, source, method, dashboard, findings, limitations and next action.

Prepare for analyst work

Practise reporting, resume, portfolio, interview and application workflows without outcome guarantees.

The PARTH DECIDE Method

One repeatable workflow for every analysis

DECIDE keeps the learner focused on the business question, evidence quality and the decision—not decorative charts.

D
DECIDE STAGE D

Define the decision

Start with the business decision, user, KPI and action—not with a chart.

What decision should this analysis improve?
Output: Decision brief and KPI definition

DECIDE is a practical teaching framework. It does not guarantee a particular job, employer decision or business outcome.

Your learning journey

From guided foundations to a business capstone

  1. 01UnderstandQuestions, KPIs and data literacy
  2. 02PrepareExcel, cleaning and Power Query
  3. 03QuerySQL and practical statistics
  4. 04VisualisePower BI, DAX and storytelling
  5. 05AutomatePython and responsible AI
  6. 06PresentPortfolio, capstone and career prep
Complete curriculum

12 modules from business questions to portfolio-ready analysis

Open any module to review its topics, practical work and documented deliverable.

Key topics
  • What data analysts do.
  • Analyst, BI analyst, MIS, reporting analyst and related role
  • Data types and data sources.
  • Descriptive, diagnostic, predictive and prescriptive analytics.
  • Stakeholders, business questions and KPIs.
  • The Parth DECIDE Method.
  • Scope, assumptions, constraints and documentation.
Practical

Convert a vague management request into measurable questions.

Deliverable

Business question and KPI brief.

Key topics
  • Data tables, formatting and validation.
  • Text, date, logical and statistical functions.
  • XLOOKUP or appropriate lookup methods.
  • INDEX and MATCH concepts.
  • SUMIFS, COUNTIFS and conditional calculations.
  • Pivot tables and pivot charts.
  • Conditional formatting.
  • Data cleaning and error checks.
  • Dashboard layout.
  • Power Query introduction.
  • AI-assisted formula explanation and debugging.
Practical

Clean a sales dataset and create an executive spreadsheet report.

Deliverable

Excel sales-performance dashboard.

Key topics
  • Population, sample and variable.
  • Mean, median, mode and percentiles.
  • Range, variance and standard deviation.
  • Distribution and skew.
  • Outliers and data quality.
  • Correlation versus causation.
  • Sampling and bias.
  • Probability fundamentals.
  • Confidence and uncertainty.
  • Hypothesis-testing introduction.
  • Interpreting results for non-technical stakeholders.
Practical

Analyse customer or campaign data and explain what the statistics do and do not prove.

Deliverable

Statistics interpretation memo.

Key topics
  • Relational database fundamentals.
  • Tables, rows, keys and relationships.
  • SELECT, DISTINCT, WHERE and ORDER BY.
  • CASE expressions.
  • Aggregate functions.
  • GROUP BY and HAVING.
  • INNER, LEFT and other appropriate joins.
  • Subqueries.
  • Common table expressions.
  • Date, text and numeric functions.
  • Window functions.
  • Data-quality queries.
  • Business reporting queries.
  • Query readability and validation.
  • SQL interview exercises.
Practical

Analyse customer, product and order tables.

Deliverable

Documented SQL analysis file with business answers.

Key topics
  • Data profiling and data dictionaries.
  • Missing values and duplicates.
  • Incorrect types and inconsistent categories.
  • Date, currency and text standardisation.
  • Validation rules and reconciliation.
  • Combining files and tables.
  • Extract, transform and load concepts.
  • Power Query transformations.
  • Audit trails and reproducibility.
  • Privacy, permissions and responsible handling.
Practical

Repair a deliberately messy multi-source dataset.

Deliverable

Clean dataset, transformation log and quality report.

Key topics
  • Power BI Desktop and Service overview.
  • Connecting to spreadsheets, CSV and databases.
  • Power Query profiling, cleaning and transformation.
  • Star-schema concepts.
  • Fact and dimension tables.
  • Relationships and filter direction.
  • Date tables.
  • DAX measures and calculated columns.
  • Core DAX functions and context.
  • KPI cards, tables, matrices and charts.
  • Filters, slicers, drill-down and drill-through.
  • Bookmarks, tooltips and navigation.
  • Dashboard hierarchy and accessibility.
  • Performance basics.
  • Publishing, workspaces and refresh concepts.
  • Row-level security introduction.
  • Responsible use of Copilot or AI features where available.
Practical

Build an interactive ecommerce or retail dashboard.

Deliverable

Power BI report, model notes and executive summary.

Key topics
  • Python and Jupyter Notebook setup.
  • Variables, collections, conditions, loops and functions at analyst
  • NumPy concepts.
  • Pandas Series and DataFrames.
  • Importing CSV and Excel data.
  • Selecting, filtering and grouping.
  • Missing values, duplicates and data types.
  • Merging and reshaping.
  • Descriptive summaries.
  • Exploratory data analysis.
  • Matplotlib and Seaborn.
  • Simple repeatable analysis scripts.
  • AI assistance for explanations and debugging.
  • Testing AI-generated code before use.
Practical

Clean and explore a customer or operations dataset.

Deliverable

Documented Jupyter Notebook with findings and limitations.

Key topics
  • Matching charts to questions.
  • Comparison, change, distribution, relationship and composition.
  • Avoiding misleading axes and distorted visuals.
  • Colour, hierarchy, labels and accessibility.
  • Dashboard versus presentation design.
  • Executive summaries.
  • Explaining trends, segments and anomalies.
  • Moving from observation to insight.
  • Building recommendations with evidence.
  • Presenting to business stakeholders.
Practical

Redesign a confusing dashboard and deliver a five-minute insight presentation.

Deliverable

Before-and-after dashboard critique and presentation.

Key topics
  • Where AI can assist the analysis workflow.
  • Dataset and column explanation.
  • Formula, SQL and Python assistance.
  • Generating analysis questions.
  • Suggesting cleaning checks.
  • Exploratory-analysis support.
  • Summarising findings.
  • Drafting narrative commentary.
  • Chart and dashboard ideation.
  • Hallucinations and arithmetic errors.
  • Validation against source data.
  • Reproducibility and prompt logging.
  • Bias, privacy and confidential data.
  • Human accountability for decisions.
Practical

Compare an AI-generated analysis with verified calculations and source evidence.

Deliverable

AI analysis validation sheet.

Key topics
  • Measurement plans and event concepts.
  • GA4 reports and explorations at an approved level.
  • Google Search Console performance data.
  • Looker Studio data sources and calculated fields.
  • Website and landing-page analysis.
  • Funnel and conversion reporting.
  • Customer acquisition cost.
  • ROAS and revenue reporting.
  • SEO and content dashboards.
  • Campaign pacing and channel comparison.
  • Attribution limitations.
  • Turning metrics into marketing actions.
Practical

Build a marketing performance dashboard using approved sample data.

Deliverable

GA4 or Looker Studio reporting case study.

Key topics
  • Ecommerce sales and product performance.
  • Marketing funnel and campaign efficiency.
  • Sales pipeline and territory reporting.
  • Finance budget-versus-actual reporting.
  • Inventory and stock movement.
  • Operations turnaround time and productivity.
  • Customer retention and churn indicators.
  • HR attendance, hiring or workforce reporting with privacy safeguards.
Practical

Select one domain, define KPIs and build a decision-oriented report.

Deliverable

Industry analysis brief and dashboard.

Key topics
  • Selecting portfolio projects.
  • Writing project problem statements.
  • Documenting data source, cleaning, method and limitations.
  • GitHub, Notion or approved portfolio platform.
  • Resume and LinkedIn project presentation.
  • Excel and SQL assessment practice.
  • Power BI and dashboard assignments.
  • Case-study and stakeholder questions.
  • Mock presentations and interviews.
  • Job-search planning.
  • Ethical representation of projects and skills.
Practical

End-to-end business analysis using the DECIDE Method.

Deliverable

Portfolio, capstone presentation and 30-day career action plan.

AI for data analysts

Use AI as an assistant—not an authority

Learners may use approved AI tools to explain formulas, draft SQL or Python, explore approaches and improve reporting. Every output still needs human verification.

Protect confidential data

Do not upload employer, client, customer, personal or company data into public AI systems without explicit permission and an approved process.

Prompt with context

State the schema, question, constraints and expected output.

Validate every result

Test formulas and code; inspect logic, edge cases and totals.

Document assistance

Record where AI helped and what a human verified.

Keep accountability

The analyst remains responsible for accuracy and privacy.

Portfolio project system

Six projects that show how you think

Each project documents the business question, data source, cleaning, method, dashboard, findings, limitations and recommendation.

PROJECT 01

Excel sales performance dashboard

Data:
Tools:
PROJECT 02

SQL customer and order analysis

Data:
Tools:
PROJECT 03

Power BI ecommerce performance dashboard

Data:
Tools:
PROJECT 04

Python data cleaning and exploratory analysis

Data:
Tools:
PROJECT 05

Marketing analytics dashboard

Data:
Tools:
PROJECT 06

Final business analytics capstone

Data:
Tools:
Portfolio integrity

Projects use public, fictional, simulated or permission-cleared data. “Real-world” describes the workflow—not unauthorised access to company information.

Tool ecosystem

Learn the tools as one connected analyst workflow

Interfaces change. Transferable concepts—data quality, modelling, analysis, visual hierarchy and communication—remain central.

Spreadsheets

Excel, Google Sheets and Power Query

Guided application

Databases

SQL querying, joins, CTEs and windows

Guided application

Business intelligence

Power BI, DAX and publishing concepts

Guided application

Python analytics

Jupyter, Pandas, NumPy, Matplotlib and Seaborn

Guided application

Marketing reporting

GA4, Search Console and Looker Studio

Guided application

AI assistance

Approved tools for formula, code and explanation support

Guided application
Industry applications

Practise analysis across real business questions

01

Ecommerce

Track revenue, conversion, product, customer and fulfilment patterns.

02

Marketing

Connect acquisition, campaign, funnel and channel performance.

03

Sales

Review targets, pipelines, territories, products and customer segments.

04

Finance reporting

Build transparent summaries for budgets, variance and management reporting.

05

Operations

Find delays, bottlenecks, quality issues and service-level trends.

06

Customer

Explore cohorts, repeat behaviour, retention and support patterns.

07

HR reporting

Create responsible workforce dashboards using permission-cleared data.

Who should join

A practical pathway for technical and non-technical learners

Prior coding is not required. Regular computer access, logical thinking and consistent practice matter.

Students & graduates

Build a structured foundation in business analysis, tools and portfolio evidence.

Counselling confirms fit

Working professionals

Add reporting and decision-support capability to your present role.

Counselling confirms fit

Digital marketers

Connect GA4, Search Console and campaign reporting with SQL, Power BI and Python.

Counselling confirms fit

MIS & reporting teams

Move from repetitive reports to cleaner models, dashboards and clearer insights.

Counselling confirms fit

Owners & managers

Improve KPI definitions, reporting quality and evidence-led decisions.

Counselling confirms fit

Career changers

Follow a guided beginner pathway with regular practice and feedback.

Counselling confirms fit
No prior coding requiredSQL and Python begin from guided foundations.
Regular practice requiredProgress comes from completing exercises and projects.
Computer access neededConfirm the current laptop and lab policy.
Practical delivery

Small-batch learning with feedback built in

01ConceptUnderstand why
02DemoSee the workflow
03PracticeApply with guidance
04ReviewCorrect the logic
05ProjectDocument evidence
Delivery facts

Details confirmed before enrolment

Current schedule, duration, mode, teaching language, trainer and tool-access arrangements are confirmed during counselling. This keeps the page honest as batches change.

  • Maximum five learners per approved batch
  • Guided labs, assignments and portfolio reviews
  • Attendance and assessment criteria apply
Why PARTH SKILLS

A sober, evidence-led learning experience

Business-first curriculum

Questions, KPIs and decisions lead every tool.

Complete analyst stack

Excel, SQL, Power BI, Python, AI and storytelling.

Maximum-five batch model

A smaller approved batch supports practical review.

Six documented projects

Build structured evidence, not copied screenshots.

Responsible AI integration

Privacy, validation and accountability are explicit.

Marketing analytics depth

Connect acquisition reporting with the wider stack.

Transparent career support

Portfolio, resume and interview guidance without guarantees.

Completion certificate

PARTH SKILLS certificate after approved criteria are met.

Trainer profile

Learn with a practitioner aligned to the approved programme

The current trainer’s verified name, role, experience, specialisms and public professional profile are shared before enrolment. This page does not publish placeholder credentials.

Current batch trainerVerified details shared during counselling
Completion certificate

PARTH SKILLS

Professional Data Analytics & AI Program

Awarded after approved attendance and assessment criteria
This is a PARTH SKILLS course-completion certificate—not a government, university, Microsoft, Google or other vendor credential.
Career applications

Where these skills may be relevant

Role fit depends on your education, prior experience, portfolio, communication, location, employer criteria and the job market.

Junior Data Analyst Reporting Analyst MIS Executive Power BI Analyst BI Analyst Marketing Analyst Ecommerce Analyst Operations Analyst Dashboard Executive

Career-readiness support

  • Portfolio structure and project explanation
  • Resume and LinkedIn review guidance
  • Interview and case-question practice
  • Application strategy and role research

No placement, interview, salary, freelance income or employment result is guaranteed.

Choose deliberately

More support than a typical self-paced recorded course

TYPICAL RECORDED COURSE

Watch demonstrations at your own pace.

Feedback, local guidance, project review and accountability may be limited or unavailable.
PARTH SKILLS PROPOSED PROGRAMME

Learn, practise, receive feedback and document decisions.

Small-batch sessions, guided labs, six projects and transparent career preparation—subject to approved batch details.
Programme facts

Confirm the right batch before you enrol

No false discount, countdown timer or invented urgency. Current operational details are shared transparently.

Professional programme

Data Analytics & AI

Current feeDiscuss during counselling
  • 12 curriculum modules
  • 6 documented portfolio projects
  • Maximum 5 learners per approved batch
  • Completion certificate criteria apply
Before enrolment

Receive the current programme sheet

Duration & scheduleConfirmed for the current batchMode & languageConfirmed during counsellingTrainerVerified profile sharedTools & laptopCurrent access policy explainedCertificateAttendance and assessment criteriaCareer supportScope explained without guarantees
Visit us in Jaipur

Meet the team before choosing your batch

Discuss your goal, background, availability and the current approved course details.

PARTH SKILLS

B77, Gaushala, Pratap Nagar, Sanganer, Jaipur, Rajasthan 302033

Confirm current counselling hours before visiting.
Pratap Nagar, SanganerJaipur, Rajasthan
B77, Gaushala
Free course counselling

Is this the right analytics pathway for you?

Share your starting point and goal. We will help you understand fit, prerequisites and the current approved batch details.

No invented urgency Clear curriculum and project scope Honest career-support boundaries
“Choose the programme after comparing the curriculum, trainer, projects, feedback model and verified operational details.”
Request course detailsRequired fields are marked *

Never send passwords, employer data, customer data or private analytics through this form.

The proposed programme includes business analytics foundations, advanced Excel, practical statistics, SQL, data cleaning, Power BI, Python with Pandas, data visualisation, responsible AI assistance, marketing analytics, six projects and career preparation.

Yes. The page targets both data analytics and data analyst search intent. The curriculum is designed around the applied workflow expected in entry-level analysis and business-intelligence work.

The right course depends on your goal, schedule, prior knowledge, trainer quality, projects and support. Compare the curriculum depth, practical assignments, trainer credentials, Power BI coverage, portfolio requirements and claims before enrolling.

Yes, many analytics tasks can be learned from a non-technical starting point. Progress depends on logical thinking, regular practice, comfort with data and the ability to explain business findings.

Prior coding is not required. SQL and Python are taught from guided foundations. Learners still need to practise syntax and problem solving.

No advanced mathematics is required for the proposed beginner pathway. Practical percentages, averages, variation, probability and interpretation are included. More advanced data science roles may require deeper mathematics.

Excel, SQL and Power BI can support many analyst tasks, but Python expands cleaning, exploration and repeatable analysis capability. This programme includes Python at practical analyst depth.

Yes. Power BI is a major module covering Power Query, data modelling, DAX, visuals, dashboards, publishing concepts and basic governance.

The Power BI module supports many relevant skills, but formal PL-300 preparation is not claimed. The PARTH SKILLS completion certificate is not the Microsoft PL-300 credential.

Yes. SQL topics include filtering, grouping, joins, subqueries, CTEs, window functions, data-quality queries and business reporting exercises.

The module covers analysis-focused spreadsheet skills including cleaning, formulas, lookups, pivot tables, charts, validation, dashboards and Power Query basics. Counselling confirms the best starting point for your current level.

Tableau is not part of the recommended core because the programme already includes substantial Power BI depth. Current optional tool coverage is confirmed during counselling.

Data analytics focuses on cleaning, querying, reporting, visualising and explaining data for decisions. Data science commonly includes more advanced statistics, machine learning and predictive modelling.

Yes. Learners use approved AI tools for formula, SQL, Python, analysis and reporting assistance. They also learn validation, privacy, hallucination checks and human accountability.

Only with explicit permission and an approved process. Confidential, personal, client or employer data must not be uploaded to public AI systems casually.

The final approved duration and schedule are confirmed during counselling. This protects learners from relying on outdated batch information.

Current classroom, live-online or hybrid availability is confirmed during counselling. The Jaipur centre is in Pratap Nagar, Sanganer.

Parth Skills’ approved model is a maximum of five learners per batch. This supports feedback but does not guarantee an individual result.

The proposed portfolio includes an Excel sales dashboard, SQL customer analysis, Power BI ecommerce dashboard, Python exploratory analysis, marketing analytics dashboard and final business capstone.

Projects use public, fictional, simulated or permission-cleared data. “Real-world” means the business problem and workflow are realistic; it does not permit unauthorised use of confidential data.

Yes. Learners document the problem, data, cleaning, method, dashboard, findings, limitations and recommendations. Portfolio publication must respect licences and privacy.

Learners who meet approved attendance and assessment criteria receive a Parth Skills course-completion certificate. It is not a vendor or government credential unless specifically verified.

Regular computer access is important for analytics practice. The current laptop and lab-access policy is confirmed before enrolment.

Current course fees, applicable taxes and approved instalment options are shared transparently during counselling.

Career support may include portfolio, resume, interview and application guidance according to the current approved programme. Placement, interview and job outcomes are not guaranteed.

No responsible institute can control an employer’s hiring decision. Skills, portfolio, education, experience, communication, location, job market and interview performance all matter.

Depending on your background and demonstrated skills, relevant areas may include junior data analysis, MIS, reporting, Power BI, marketing analytics, ecommerce analytics and operations reporting. Employers define their own requirements.

It can provide skill foundations after 12th, subject to counselling and approved eligibility. Some employers may require graduation for particular roles.

Yes, subject to counselling and readiness for regular practice. Business-domain knowledge can be valuable in analytics when combined with technical and communication skills.

Yes. The programme can add business analysis, dashboard and stakeholder-communication practice to a technical background.

Yes, if an approved schedule matches their availability. Working professionals should not use employer data without permission.

Yes. The marketing analytics module builds on GA4, Search Console, Looker Studio, funnel, acquisition and campaign reporting while adding SQL, Power BI and Python.

Yes. Learners practise choosing visuals, creating hierarchy, writing executive summaries, explaining uncertainty and presenting recommendations.

Yes. The module covers descriptive statistics, variation, distribution, outliers, sampling, correlation and an introduction to hypothesis testing, with emphasis on interpretation.

Yes. Dashboard design is taught in Excel, Power BI and storytelling modules, including audience, hierarchy, chart choice, filters, accessibility and recommendations.

Yes, when the owner wants to improve KPI definitions, reporting and decision making. The complete technical programme may be more detailed than a short executive workshop.

Current teaching-language options are confirmed during counselling. Technical terms and software interfaces may remain in English.

The current make-up, recording and attendance policy is explained before enrolment. Lifetime recordings or unlimited backup classes are not promised unless they are part of the approved batch policy.

Some tools have free or trial options, while others may require licences depending on use. Counselling confirms what PARTH SKILLS provides and what the learner needs to arrange.

Parth Skills is at B77, Gaushala, Pratap Nagar, Sanganer, Jaipur, Rajasthan 302033. Confirm current counselling hours before visiting.

Your next decision

Build analytics skills that move your work forward

Start with the right question, learn the connected tool stack and finish with portfolio evidence you can explain.

No job, placement, salary or career-outcome guarantee.
DECIDE