Online Internship Program in Data Analytics Using AI/ML

This online internship is designed for university students to gain real-world exposure in the field of Data Analytics powered by Artificial Intelligence and Machine Learning. The program blends academic concepts with hands-on learning through industry-based projects. Participants will build practical skills in data processing, statistical analysis, predictive modeling, and AI/ML tools.

Detailed Course Content:

Module 1: Fundamentals of Data Analytics

• Introduction to Data Analytics and its Business Value
• Data Types, Sources, and Lifecycle
• Data Collection and Cleaning Techniques
• Exploratory Data Analysis (EDA)

Module 2: Tools and Technologies

• Excel, SQL Basics, and Data Manipulation
• Introduction to Python/R for Data Analysis
• Using Jupyter Notebooks for Reporting
• Introduction to Data Visualization Tools (Tableau/Power BI)

Module 3: Machine Learning Basics

• Overview of AI and ML
• Supervised vs Unsupervised Learning
• Regression, Classification, and Clustering
• Introduction to Scikit-learn and TensorFlow

Module 4: Data-Driven Decision Making

• Business Intelligence Concepts
• KPI Selection and Measurement
• Building Dashboards for Business Insights
• Communicating Data Findings Effectively

Module 5: Real-World Data Analytics Techniques

• Feature Engineering and Model Evaluation
• Data Pipelines and Automation Concepts
• A/B Testing and Hypothesis Testing
• Dealing with Imbalanced Data and Bias

Module 6: Ethics and Governance in AI

• Data Privacy and Protection (GDPR, HIPAA overview)
• Responsible AI and Algorithmic Fairness
• AI Governance Policies and Challenges

Module 7: Capstone Project Implementation and Presentation

• Team Collaboration and Agile Tools (Trello/Slack)
• Milestone Planning and Reporting
• Presentation Skills and Storytelling with Data
• Final Project Demo and Peer Feedback

Real-Life Online Project

Project Title: Customer Churn Prediction and Retention Strategy Design
Project Brief: A fictional digital service provider is facing a high customer churn rate and seeks data-driven insights to improve customer retention. Interns will:

• Analyze historical customer behavior and transaction data.
• Identify key churn indicators using ML classification models.
• Build dashboards to visualize churn trends by geography and demographics.
• Propose intervention strategies (e.g., personalized offers, loyalty programs).
• Present a detailed report with actionable insights and AI-driven retention roadmap.

The internship concludes with each team presenting their findings, code notebooks, dashboards, and strategic recommendations to a simulated business panel.