Project Overview
- Objective: To apply data analytics and AI techniques to a real-world problem or dataset, demonstrating the ability to gather, analyze, interpret, and present data.
- Scope: Projects can be individual or group-based, focusing on industries like finance, healthcare, retail, or any sector relevant to the students’ interests or local economic needs.
Stages of the Project
Stage 1: Project Proposal
- Deliverables:
- Project title and team members (if applicable)
- A clear statement of the problem
- Objectives and expected outcomes
- Preliminary research and existing solutions
Stage 2: Data Collection and Preparation
- Deliverables:
- Description of data sources
- Data collection methodology
- Data cleaning and preprocessing steps
Stage 3: Exploratory Data Analysis
- Deliverables:
- Statistical summaries and visualizations of the data
- Initial insights and hypotheses based on the data
Stage 4: Model Development
- Deliverables:
- Selection of appropriate AI and machine learning models
- Training models and tuning parameters
- Validation and testing of models
Stage 5: Results and Interpretation
- Deliverables:
- Detailed analysis of model results
- Comparison with initial hypotheses and objectives
- Discussion of the model’s effectiveness and limitations
Stage 6: Final Presentation and Report
- Deliverables:
- Comprehensive report documenting all stages of the project
- Presentation of the project outcomes to an audience which may include peers, faculty, and industry professionals
This structured approach ensures thorough exploration and application of data analytics and AI techniques throughout the project lifecycle.
