| Stage | Objective | Deadline | Remark | Progress |
| Sem 1 | ||||
| Project Setup (4 Weeks) | Feasibility Assessment | 9/22 | Identify the possible data source. Identify APIs to collect market data and news. Identify languages and tech stacks applied. | Completed |
| Environment Setup | 10/1 | Select programming languages and tools Setup development environment and necessary libraries | Completed | |
| Project Website Creation | 10/1 | Updated with Each Milestone | Completed | |
| Detailed Project Plan | 10/1 | Completed | ||
| Preliminary Study (5 Weeks) | Milestone1: Preliminary Research Summary | 10/31 | Milestone Deliverable: Preliminary Study Summary (Will be updated on Webpage) | On Progress |
| * Simultaneous work on Data Manipulation & ML implementation | ||||
| Dataset Manipulation (8 Weeks) | Data Collection/Prepare Dataset | 12/31 | Collect historical cryptocurrency market data. Collect news articles and social media posts related to cryptocurrencies. Find dataset with cryptocurrency market data and news | |
| Data preprocessing/cleaning | 12/31 | Brainstorm as many features as possible Generate some features by LLM Cleaning, normalization, and structuring for future analysis. | ||
| ML Implementation (8 Weeks) | Train models using both historical market indicators and news | 12/31 | Choose appropriate machine learning models based on preliminary study. Split data into training, validation, and test sets. | |
| Milestone 2: Pave the path for research | 12/31 | Ensure models can be trained with limited data and limited features | ||
| Sem 2 | ||||
| Midterm Wrap-up (3 weeks) | First Presentation | 1/13 | Midterm Paperwork No workload allocated in winter holiday | |
| Interim Report | 1/26 | |||
| * Simultaneous work on ML Model Reinforcement and Testing & UI Implementation | ||||
| ML Model Reinforcement and Testing (8 Weeks) | Feature Selection & Models Comparison | Try different feature groups and find the most relation features Try different combinations of tested and predicted time and find the model with the best combination | ||
| Reinforce Models | Implement advanced techniques like cross-validation to avoid overfitting. (To be confirmed by the assessment result) Iterative work on feature selection, hyperparameter tuning and validation to optimize performance. | |||
| Milestone 3: Finalize ML Model | 3/17 | Milestone Deliverable: Predictive models which are well developed and evaluated | ||
| UI Implementation (8 Weeks) | Frontend Development | Design UI and Implement the frontend with React | ||
| Integration with ML models | Connect the frontend with the machine learning model through a backend in Django / Flask | |||
| Milestone 4: Finish all coding deliverables | 3/17 | Milestone Deliverable: A functional UI developed and integrated with the models. | ||
| Final Wrap-Up (5 Weeks) | Final Individual Report | 4/21 | Final Paperwork Another extra report focusing on the project details should be written by the group | |
| Final Presentation | 4/21 | |||
| Final Project Website | 4/30 | |||
| Final Report | 5/30 | |||