Gaurav Vaishnav

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Gaurav Vaishnav

Computer Science · Shri Vishwakarma Skill University

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Projects

Certified

Self-directed project

Business Analytics Sprint

Data Science · August 2026

91/ 100

A ProoV case study · educational project, not employment

Built an end-to-end profit investigation that started with structured hypotheses and a data audit, then validated the core drivers with SQL, pivot analysis, and a Pareto-style root-cause ranking. The work culminated in a boardroom-ready recommendation set and executive summary that linked discount discipline, logistics efficiency, and raw-material cost control to a credible recovery path.

Graded against

  • Problem Framing & Hypotheses10%
  • Data Analysis & SQL30%
  • Root-Cause & Forecasting25%
  • Dashboard & Visualization15%
  • Executive Communication & Strategy20%

Passed · pass mark 60/100

What stood out6
  • Built a structurally sound hypothesis set around raw materials, logistics, and discounting before analysis
  • Computed category margin with the correct revenue-minus-cost logic and grouped by category
  • Used a joined regional query to connect margin with discount behavior
  • Translated the analysis into a prioritized boardroom narrative with clear growth-versus-profit framing
  • Leakage-Free Problem Framing
  • Correct SQL Aggregation and Join Logic
The work I submitted20 tasks

12 tasks · 4.8k characters · 8 written answers · 248 words

  • Hypothesis Sheet890 characters
  • KPI Driver Map174 characters
  • Data Audit100 characters
  • Week1 Update648 characters
  • Sql Category Profit297 characters
  • Sql Region Join367 characters
  • Dashboard58 characters
  • Root Causes158 characters
  • Forecast274 characters
  • AI Reflection205 characters
  • Recommendations964 characters
  • Boardroom Deck651 characters
  • Hypothesis Sheet98 words
  • KPI Driver Map1 word
  • Data Audit4 words
  • Week1 Update93 words
  • Sql Category Profit19 words
  • Sql Region Join27 words
  • Dashboard1 word
  • Root Causes5 words

Summarised on purpose — the submitted code and writing stay private so this page cannot be reused as an answer key. The full submission sits behind the verified certificate.

Verified certificateTamper-proof · issued by ProoV
Certified

Self-directed project

Data Analytics and AI

Data Science · June 2026

84/ 100

A ProoV case study · educational project, not employment

A verified, self-directed industry project — completed and passed a real industry rubric at 84/100 on ProoV.

Graded against

  • Exploratory Data Analysis20%
  • Time-Series Analysis25%
  • Forecasting Model Building35%
  • Business Communication20%

Passed · pass mark 60/100

What stood out6
  • Compared three forecasting approaches with MAE, RMSE, and MAPE on a sequential holdout split
  • Correctly identified SARIMA as the strongest model for seasonal demand forecasting
  • Produced meaningful regional and product/channel insights tied to retail strategy
  • Used decomposition, moving averages, and ACF to support time-series interpretation
  • Data-Driven Decision Making
  • Time-Series Analysis
The work I submitted20 tasks

12 tasks · 11.7k characters · Python · 8 written answers · 595 words

  • Setup Resource DeliveryPython · 1.0k characters
  • Eda Code 1 LoadPython · 1.6k characters
  • Eda Step 1 Load410 characters
  • Eda Code 1 Describe2.0k characters
  • Eda Step 1 Describe481 characters
  • Eda Code 1 Timeseries880 characters
  • Eda Step 1 Timeseries460 characters
  • Eda Code 1 Regional1.1k characters
  • Eda Step 1 Regional600 characters
  • Eda Code 1 Product1.6k characters
  • Ts Code 2 Resample1.2k characters
  • Ts Step 2 Resample432 characters
  • Setup Resource Delivery84 words
  • Eda Code 1 Load101 words
  • Eda Step 1 Load54 words
  • Eda Code 1 Describe90 words
  • Eda Step 1 Describe61 words
  • Eda Code 1 Timeseries65 words
  • Eda Step 1 Timeseries61 words
  • Eda Code 1 Regional79 words

Summarised on purpose — the submitted code and writing stay private so this page cannot be reused as an answer key. The full submission sits behind the verified certificate.

Verified certificateTamper-proof · issued by ProoV
Certified

Self-directed project

Machine Learning for Automotive

AI / ML · June 2026

86/ 100

A ProoV case study · educational project, not employment

A verified, self-directed industry project — completed and passed a real industry rubric at 86/100 on ProoV.

Graded against

  • Exploratory Data Analysis20%
  • Feature Engineering25%
  • Model Building & Evaluation35%
  • Business Communication20%

Passed · pass mark 60/100

What stood out6
  • Correctly identified that Random Forest substantially outperformed Linear Regression on R² and MAE.
  • Highlighted the most important pricing drivers, including MPG, car age, and engine size.
  • Connected model performance to a concrete CPO business impact estimate and pricing recommendation.
  • Demonstrated useful EDA insights, including Audi's price premium over VW.
  • Data-Driven Decision Making
  • Feature Engineering
The work I submitted10 tasks

5 tasks · 6 lines · 5 written answers · 166 words

  • VW Sprint1 Complete56 characters
  • VW Sprint2 Complete61 characters
  • VW Sprint3 Complete59 characters
  • VW Business Insights1.3k characters
  • Jupyterlite Code2 lines
  • VW Sprint1 Complete1 word
  • VW Sprint2 Complete1 word
  • VW Sprint3 Complete1 word
  • VW Business Insights162 words
  • Jupyterlite Code1 word

Summarised on purpose — the submitted code and writing stay private so this page cannot be reused as an answer key. The full submission sits behind the verified certificate.

Verified certificateTamper-proof · issued by ProoV
3Projects completed
3Verified certificates
87Average score
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