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.
Final trainer, schedule, duration, delivery mode, fee, teaching language and certificate criteria are confirmed during counselling. No job, salary or placement outcome is guaranteed.
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.
What changed?
Compare actual performance with a useful baseline.
Why did it change?
Segment, investigate and test reasonable explanations.
What needs attention?
Surface risk, quality issues and meaningful exceptions.
What should happen next?
Translate findings into an accountable recommendation.
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.
The programme teaches tools as part of a responsible decision workflow.
Prepare
Clean, reshape and connect reliable data.
Analyse
Compare patterns, KPIs and segments.
Explain
Build a dashboard and recommend action.
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.
One repeatable workflow for every analysis
DECIDE keeps the learner focused on the business question, evidence quality and the decision—not decorative charts.
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.
From guided foundations to a business capstone
- 01UnderstandQuestions, KPIs and data literacy
- 02PrepareExcel, cleaning and Power Query
- 03QuerySQL and practical statistics
- 04VisualisePower BI, DAX and storytelling
- 05AutomatePython and responsible AI
- 06PresentPortfolio, capstone and career prep
12 modules from business questions to portfolio-ready analysis
Open any module to review its topics, practical work and documented deliverable.
- 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.
Convert a vague management request into measurable questions.
Business question and KPI brief.
- 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.
Clean a sales dataset and create an executive spreadsheet report.
Excel sales-performance dashboard.
- 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.
Analyse customer or campaign data and explain what the statistics do and do not prove.
Statistics interpretation memo.
- 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.
Analyse customer, product and order tables.
Documented SQL analysis file with business answers.
- 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.
Repair a deliberately messy multi-source dataset.
Clean dataset, transformation log and quality report.
- 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.
Build an interactive ecommerce or retail dashboard.
Power BI report, model notes and executive summary.
- 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.
Clean and explore a customer or operations dataset.
Documented Jupyter Notebook with findings and limitations.
- 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.
Redesign a confusing dashboard and deliver a five-minute insight presentation.
Before-and-after dashboard critique and presentation.
- 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.
Compare an AI-generated analysis with verified calculations and source evidence.
AI analysis validation sheet.
- 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.
Build a marketing performance dashboard using approved sample data.
GA4 or Looker Studio reporting case study.
- 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.
Select one domain, define KPIs and build a decision-oriented report.
Industry analysis brief and dashboard.
- 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.
End-to-end business analysis using the DECIDE Method.
Portfolio, capstone presentation and 30-day career action plan.
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.
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.
Six projects that show how you think
Each project documents the business question, data source, cleaning, method, dashboard, findings, limitations and recommendation.
Excel sales performance dashboard
Data:Tools:
SQL customer and order analysis
Data:Tools:
Power BI ecommerce performance dashboard
Data:Tools:
Python data cleaning and exploratory analysis
Data:Tools:
Marketing analytics dashboard
Data:Tools:
Final business analytics capstone
Data:Tools:
Projects use public, fictional, simulated or permission-cleared data. “Real-world” describes the workflow—not unauthorised access to company information.
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 applicationDatabases
SQL querying, joins, CTEs and windows
Guided applicationBusiness intelligence
Power BI, DAX and publishing concepts
Guided applicationPython analytics
Jupyter, Pandas, NumPy, Matplotlib and Seaborn
Guided applicationMarketing reporting
GA4, Search Console and Looker Studio
Guided applicationAI assistance
Approved tools for formula, code and explanation support
Guided applicationPractise analysis across real business questions
Ecommerce
Track revenue, conversion, product, customer and fulfilment patterns.
Marketing
Connect acquisition, campaign, funnel and channel performance.
Sales
Review targets, pipelines, territories, products and customer segments.
Finance reporting
Build transparent summaries for budgets, variance and management reporting.
Operations
Find delays, bottlenecks, quality issues and service-level trends.
Customer
Explore cohorts, repeat behaviour, retention and support patterns.
HR reporting
Create responsible workforce dashboards using permission-cleared data.
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 fitWorking professionals
Add reporting and decision-support capability to your present role.
Counselling confirms fitDigital marketers
Connect GA4, Search Console and campaign reporting with SQL, Power BI and Python.
Counselling confirms fitMIS & reporting teams
Move from repetitive reports to cleaner models, dashboards and clearer insights.
Counselling confirms fitOwners & managers
Improve KPI definitions, reporting quality and evidence-led decisions.
Counselling confirms fitCareer changers
Follow a guided beginner pathway with regular practice and feedback.
Counselling confirms fitSmall-batch learning with feedback built in
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
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.
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.
PARTH SKILLS
Professional Data Analytics & AI Program
Where these skills may be relevant
Role fit depends on your education, prior experience, portfolio, communication, location, employer criteria and the job market.
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.
More support than a typical self-paced recorded course
Watch demonstrations at your own pace.
Feedback, local guidance, project review and accountability may be limited or unavailable.Learn, practise, receive feedback and document decisions.
Small-batch sessions, guided labs, six projects and transparent career preparation—subject to approved batch details.Confirm the right batch before you enrol
No false discount, countdown timer or invented urgency. Current operational details are shared transparently.
Data Analytics & AI
- 12 curriculum modules
- 6 documented portfolio projects
- Maximum 5 learners per approved batch
- Completion certificate criteria apply
Receive the current programme sheet
Meet the team before choosing your batch
Discuss your goal, background, availability and the current approved course details.
B77, Gaushala, Pratap Nagar, Sanganer, Jaipur, Rajasthan 302033
Confirm current counselling hours before visiting.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.
“Choose the programme after comparing the curriculum, trainer, projects, feedback model and verified operational details.”
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.
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.