Lessons
Explore all newline lessons
lesson
Orientation — Technical KickoffAI Bootcamp- Jupyter & Python Setup - Understanding why Python is used in AI (simplicity, libraries, end-to-end stack) - Exploring Jupyter Notebooks: shortcuts, code + text blocks, and cloud tools like Google Colab - Hands-On with Arrays, Vectors, and Tensors - Creating and manipulating 2D and 3D NumPy arrays (reshaping, indexing, slicing) - Performing matrix operations: element-wise math and dot products - Visualizing vectors and tensors in 2D and 3D space using matplotlib - Mathematical Foundations in Practice - Exponentiation and logarithms: visual intuition and matrix operations - Normalization techniques and why they matter in ML workflows - Activation functions: sigmoid and softmax with coding from scratch - Statistics and Real Data Practice - Exploring core stats: mean, standard deviation, normal distributions - Working with real datasets (Titanic) using Pandas: filtering, grouping, feature engineering, visualization - Preprocessing tabular data for ML: encoding, scaling, train/test split - Bonus Topics - Intro to probability, distributions, classification vs regression - Tensor intuition and compute providers (GPU, Colab, cloud vs local)
lesson
Orientation — Course IntroductionAI Bootcamp- Meet the instructors and understand the support ecosystem (Circle, Notion, async help) - Learn the 4 learning pillars: concept clarity, muscle memory, project building, and peer community - Understand course philosophy: minimize math, maximize intuition, focus on real-world relevance - Set up accountability systems, learning tools, and productivity habits for long-term success
lesson
Staying Current with AI (Research, News, and Tools)AI Bootcamp- Track foundational trends: RAG, Agents, Fine-tuning, RLHF, Infra - Understand tradeoffs of long context windows vs retrieval pipelines - Compare agent frameworks (CrewAI vs LangGraph vs Relevance AI) - Learn from real 2025 GenAI use cases: productivity + emotion-first design - Stay current via curated newsletters, YouTube breakdowns, and community tools
lesson
Career Prep — Roles, Interviews, and AI Career PathsAI Bootcamp- Break down roles: AI Engineer, Model Engineer, Researcher, PM, Architect - Prepare for FAANG/LLM interviews with DSA, behavioral prep, and project portfolio - Use ChatGPT and other tools for mock interviews and story crafting - Learn how to build a standout AI resume, repo, and demo strategy - Explore internal AI projects, indie hacker startup paths, and transition guides
lesson
RAG Hallucination Control & Enterprise SearchAI Bootcamp- Explore use of RAG in enterprise settings with citation engines - Compare hallucination reduction strategies: constrained decoding, retrieval, DPO - Evaluate model trustworthiness for sensitive applications - Learn from production examples in legal, compliance, and finance contexts
lesson
LLM Production Chain (Inference, Deployment, CI/CD)AI Bootcamp- Map the end-to-end LLM production chain: data, serving, latency, monitoring - Explore multi-tenant LLM APIs, vector databases, caching, rate limiting - Understand tradeoffs between hosting vs using APIs, and inference tuning - Plan a scalable serving stack (e.g., LLM + vector DB + API + orchestrator) - Learn about LLMOps roles, workflows, and production-level tooling