Learning Path Designer
A split view keeps the advisor and roadmap side by side. The chat stays embedded—no floating bubbles or distractions.
AI Learning Advisor
Embedded chat; grounded suggestions replace this placeholder once wired.
Advisor
Welcome. Tell me where you are starting from, and I will shape a clear path with you.
You
I know Python and stats, but I am new to modern LLMs.
Advisor
Placeholder: When the backend is wired, this advisor will propose a staged plan with checkpoints and resources that match your background.
Personalized roadmap
A calm outline to track your progress.
Foundations
Start hereClear math, programming, and data basics before touching heavier models.
- Strengthen Python + notebooks for experiments
- Probability, linear algebra, and calculus refreshers
- Data literacy: cleaning, charting, and reasoning
- Evaluate with baselines before adding complexity
Core ML
Supervised/unsupervised patterns, evaluation, and iteration discipline.
- Modeling patterns: regression, classification, trees, ensembles
- Cross-validation, leakage checks, and calibration
- Feature pipelines and monitoring basics
NLP
Classical NLP groundwork to understand why LLMs behave as they do.
- Tokenization, embeddings, and sequence models
- Information retrieval and ranking fundamentals
- Evaluation with human-in-the-loop checks
LLMs
Modern large language models with an emphasis on safety and reliability.
- Prompt design with guardrails
- Evaluation: correctness, safety, and user experience
- Model selection trade-offs and latency budgeting
RAG
Retrieval-augmented generation with grounded context and observability.
- Indexing strategies and chunking choices
- Retrieval quality checks and feedback loops
- Caching, fallbacks, and outage playbooks
Agents
Tool-use, planning, and failure containment for agentic systems.
- When to use agents vs. simpler flows
- Action orchestration, timeouts, and rollbacks
- Human override and safety gates
Placeholder copy: Once the backend is connected, this roadmap will update live based on the advisor's reasoning and your feedback.