Phase 1: Core AI/ML Foundations (0–4 Months)#
Timeline: 20 Dec 2024 to 20 April 2025
Goals:#
- Build foundational skills in AI/ML through projects and structured learning.
- Transition from day-long challenges to in-depth weeklong or biweekly projects.
Action Plan:#
Complete the 4-Month AI/ML Challenge**:
- Focus on Computer Vision, Recommender Systems, and Reinforcement Learning.
- Develop end-to-end projects with deployment.
Leverage Web Development Experience:
- Practice deploying ML models as APIs using FastAPI.
- Work with cloud platforms like AWS, GCP, or Azure to host models.
Phase 2: Build a Portfolio and Real-World Expertise (4–9 Months)#
Note: This period will be a little more hectic because of personal commitments, so keeping that in mind.
Timeline: 1 May 2025 to 30 Sep 2025
Goals:#
- Transition from learning to solving real-world problems.
Action Plan:#
- Capstone Project:
- Build an end-to-end project with real-world relevance.
- Examples:
- Computer Vision: Real-time object detection for smart cameras.
- NLP: AI-based document summarizer for businesses.
- Recommender System: Personalized book or movie recommendation engine.
Phase 3: University Preparation (9–12 Months)#
Timeline: 1 October 2025 to 30 December 2025
Goals:#
- Prepare for applications to top European master’s programs in Machine Learning.
- Build a competitive profile with projects, test scores, and compelling documents.
Action Plan:#
- Identify Target Universities and Programs:
- Research top European universities offering ML-related programs:
- Review admission requirements and deadlines.
- Refine your portfolio to showcase your expertise in AI/ML.
- Focus on projects relevant to the program’s research areas (e.g., computer vision, generative AI).
- Create a dedicated portfolio on personal website summarizing the projects.