• Tableau Dashboard – Deloitte Data Analytics Simulation
This project formed part of Deloitte’s Data Analytics Job Simulation on Forage. I acted as a junior data analyst supporting a client-facing scenario. My responsibilities included analyzing raw financial transactions in Excel, classifying risk levels, and cleaning the dataset for visualization. I used Tableau to create an interactive dashboard with filters, KPIs, and trend analyses to spotlight irregularities and highlight actionable insights. The final deliverable mimicked real consulting workflows, teaching me how to translate raw data into impactful business intelligence that drives executive decision-making.
Business Dashboard-Deloitte Technology Consulting Simulation
As part of this simulation, I took on the role of a junior technology consultant tasked with identifying and proposing IT solutions for a fictional client. I evaluated their business challenge and designed a centralized dashboard concept to help decision-makers monitor cross-department KPIs. I created a structured proposal that included the dashboard layout, rationale for technology choices, and benefits of implementation. This simulated client engagement sharpened my skills in business analysis, stakeholder communication, and IT consulting documentation.
• Python Facial Recognition System – GUVI
As part of the GUVI Python certification, I developed a facial recognition application that utilized Python’s OpenCV library to detect and identify human faces in real-time. I began by training the system on a custom image dataset using Haar Cascade classifiers. The application then used webcam input to detect faces, matched them against stored profiles, and displayed identification results with accuracy metrics. I implemented preprocessing techniques like grayscale conversion and noise reduction to enhance detection. This project gave me valuable experience in applying computer vision, machine learning basics, and real-time software development—all skills highly relevant to AI and automation roles.
• AI Foundations Project – University of Helsinki
This project explored real-world machine learning through the “Elements of AI” course. I implemented decision trees and logistic regression models using educational tools to work through classification and prediction problems. The course challenged me to think critically about model design and validation. Beyond coding, I explored algorithmic bias, the role of explainability in AI systems, and ethical frameworks for deploying intelligent technology. The experience offered foundational exposure to technical and ethical challenges in artificial intelligence.
Curious where I’ve applied these skills? Read about My Experience
Vikrant Tiwari 