🎓 Microsoft Elevate – GTU Internship (Jan–Apr 2026)

This repository documents my 12-week internship under the Microsoft Elevate Program, conducted as part of GTU 8th Semester Internship and powered by Edunet Foundation & FICE Education.

The internship focuses on Data Analytics, Machine Learning, Deep Learning, Power BI, Generative AI, and Microsoft Azure Cloud, with hands-on labs, notebooks, scripts, and real-world datasets.

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🚀 App Preview

🔗 Click here to interact with the live application: Open Live Dashboard

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📌 Internship Details

• Program: Microsoft Elevate – GTU Internship

• Duration: January 2026 – April 2026 (12 Weeks)

• Mode: Online + Hands-on Labs

• Academic Requirement: GTU 8th Semester Internship

• Powered By: Edunet Foundation & FICE Education

• Mentorship: Industry experts & Microsoft trainers

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🧠 Learning Roadmap (Week-wise)

🔹 Week 1 – Foundations

• Orientation & Registration

• Introduction to Artificial Intelligence

• Introduction to Data Analytics

🔹 Week 2 – Data Handling & Visualization

• Data Cleaning & Preprocessing

• Exploratory Data Analysis (EDA)

• Data Visualization (Matplotlib, Seaborn)

🔹 Week 3 – Business Intelligence

• Power BI Fundamentals

• Data Modeling

• DAX (Data Analysis Expressions)

🔹 Week 4 – Deep Learning Basics

• Artificial Neural Networks (ANN)

• Deep Learning Concepts

🔹 Week 5 – Advanced BI

• Advanced DAX

• Power BI Dashboard Development

🔹 Week 6 – Machine Learning

• Supervised Learning Algorithms

• Model Training & Evaluation

🔹 Week 7 – Advanced ML

• Unsupervised Learning

• Reinforcement Learning

🔹 Week 8 – Deep Learning (Advanced)

• ANN (Advanced Use Cases)

• Model Optimization

🔹 Week 9 – Computer Vision

• Convolutional Neural Networks (CNN)

• TensorFlow & Keras

🔹 Week 10 – Generative AI

• Generative AI Concepts

• Microsoft Copilot

• Prompt Engineering

🔹 Week 11 – Cloud Computing

• Cloud Fundamentals

• Microsoft Azure Introduction

🔹 Week 12 – Azure Experiments

• Azure Labs

• Cloud Experiments

• Deployment Basics

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📂 Repository Structure

MS-Elevate-Internship/

│

├── Data/                # Datasets used for analysis & ML

├── Notebooks/           # Google Colab / Jupyter notebooks

├── Scripts/             # Cleaned Python scripts (.py)

├── Session-Notes/       # Session-wise notes & learnings

├── README.md            # Project documentation

└── .gitignore           # Ignored files & folders

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🛠️ Technologies & Tools Used

Programming & Analysis

• Python

• Pandas

• NumPy

• Matplotlib

• Seaborn

Machine Learning & AI

• Scikit-learn

• TensorFlow

• Keras

• Deep Learning (ANN, CNN)

• Reinforcement Learning

• Generative AI

Business Intelligence

• Power BI

• DAX

• Dashboard Design

• Data Modeling

Cloud

• Microsoft Azure

• Azure Labs & Experiments

Dev Tools

• Google Colab

• VS Code

• Git & GitHub

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🎯 What This Repository Shows

• My learning journey during the internship

• Hands-on data analysis & ML workflows

• Clean conversion of notebooks → scripts

• Real-world dataset handling

• Structured project organization

• Industry-ready coding practices

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🚀 Outcome

By the end of this internship, I gained:

• Strong foundation in Data Analytics & AI

• Practical exposure to Machine Learning & Deep Learning

• Experience with Power BI & Business Intelligence

• Hands-on knowledge of Azure Cloud

• Confidence in end-to-end data projects

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📌 Author

Gulam Ali Khorajiya

GTU 8th Semester Student

Microsoft Elevate Intern (2026)

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⭐ This repository represents my consistent effort, learning discipline, and growth throughout the Microsoft Elevate Internship.