Information About Habib - Worcester Park trainer

Personal Description:

Ex-Meta Senior Full-Stack Engineer with over 5 years of experience delivering scalable software solutions, enabling hyper-growth and multi-million-dollar fundraises. Having started coding at age 12, I have a proven track record of building MVPs ahead of schedule, optimizing engineering processes, and scaling products from concept to 100k+ users. Expertise spans across SaaS platforms, AI/ML/LLMs, Web3 & healthcare.

As a computer science educator, I bring a unique blend of 8+ years of teaching experience and 5+ years of hands-on industry expertise to technical training. My career spans curriculum design for university programs, mentorship at a FAANG company, and open-source contributions to projects like Electronj.js. This dual perspective allows me to demystify complex concepts while grounding lessons in real-world system design challenges, from distributed systems to machine learning infrastructure. I specialize in transforming abstract theory into actionable engineering skills, with a focus on algorithmic thinking, performance optimization, and modern development practices.

Training Experience:

• University Level: Designed and delivered courses in algorithms, data structures, and systems programming for 500+ undergraduate/graduate students at Imperial College London and University of Toronto
• Corporate Training: Led Meta’s internal engineering bootcamps on production-grade coding practices, reducing onboarding time for new hires by 40% through project-based learning
• Specialized Workshops: Created immersive programs in:
• Distributed systems architecture (Kafka, Kubernetes)
• Machine learning engineering (TFX, PyTorch deployment)
• Interview preparation (LeetCode mastery, system design simulations)
• Key Achievements:
• 92% success rate for students securing FAANG positions
• Developed adaptive learning system using LLMs to personalize coding exercises

Training Approach:

My methodology combines three pillars:

1. Conceptual Foundations
• Teach first-principles thinking through SICP-inspired problem solving
• Map abstract CS concepts to concrete engineering tradeoffs (e.g… time/space complexity vs cloud costs)
• Use live coding sessions to demonstrate iterative debugging processes
2. Active Learning
• Project-driven curriculum with Git-based code reviews mirroring industry workflows
• Example: Build a Redis clone in Rust
• Example: Optimize ML pipeline latency by 50%
• Pair programming exercises focusing on:
• API design patterns
• Performance profiling
• Test-driven development
3. Industry-Aligned Skills
• Practical industry-backe skills