← Fellowship Prep Guide
The Knowledge House · Innovation Fellowship
AI Business Solutions Track
AI Business Solutions track
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In Phase 1 (Feb–May) you'll build foundational programming, data, and interface skills; in Phase 2 (June–Aug) you'll go deeper into machine learning, natural language processing, and AI agents, building toward a capstone that combines retrieval-augmented generation (RAG) with a fine-tuned model.
Phase 1 tools
| Tool | Why you need it | Link | Cost |
|---|---|---|---|
| NumPy | Python library for numerical computing, used throughout the data and machine learning coursework. | Free | |
| Pandas | Python library for working with structured datasets — you'll use this constantly for data handling. | Free | |
| Figma | Where you'll design user-centered interfaces before building them. | Freemium Free tier available. | |
| Lovable | You'll use this to turn Figma designs into working frontend webpages, and later to visualize data. | Freemium Free tier available. | |
| SQLTools (VS Code extension) | A SQL client inside VS Code for practicing SELECT/INSERT/UPDATE/DELETE queries and database seeding. | Free | |
| Pytest | Python's standard testing framework — used when you package applications and write unit tests. | Free | |
| Pydantic | Used for creating structured data models, covered when you build customer-interaction data models. | Free | |
| scikit-learn | Your introduction to building simple machine learning models in Python. | Free |
Phase 2 tools (deep learning, NLP & AI agents)
| Tool | Why you need it | Link | Cost |
|---|---|---|---|
| Keras | Used to build sequential neural network models, starting with a digit-classification project. | Free | |
| NLTK | One of three libraries used to learn tokenization — how computers break text into processable units. | Free | |
| spaCy | The second tokenization library you'll work with. | Free | |
| Hugging Face | The third tokenization library, and your entry point into pretrained NLP models generally. | Freemium Free tier available. | |
| FAISS | The vector database you'll implement for semantic search over documents — core to your RAG capstone. | Free | |
| LangChain | The framework you'll use to build AI agent workflows — chaining prompts, tools, and memory together. | Freemium Free tier available. |