🎯 2-Week Intensive Roadmap
Week 1: Core Skills
Days 1-2: Coursera Gen AI with LLMs (free audit)
- Maps to JD: "Design, develop, and implement machine learning models and AI solutions" + "In-depth knowledge of Generative AI and NLP techniques"
Days 3-4: LangChain RAG Tutorial + OpenAI Quickstart
- Maps to JD: "Experience in Large Language Model (LLM) tuning (OpenAI preferred)" + "Developing AI agents for automating decision-making"
Days 5-7: Build first RAG project using this guide
- Maps to JD: "Implement NLP techniques for analyzing and extracting insights from textual data" + "Drive end-to-end machine learning workflows"
Week 2: Portfolio + Practice
Days 8-10: Complete 2 projects from datasets below
- Maps to JD: "Solid understanding of supervised and unsupervised machine learning techniques" + "Model evaluation, validation, and performance metrics"
Days 11-12: Study papers + mock interviews
- Maps to JD: "Ability to communicate complex technical concepts to both technical and non-technical stakeholders"
Days 13-14: Deploy one project, polish GitHub
- Maps to JD: "Build and maintain scalable solutions using technologies such as Python, MongoDB, and Databricks"
🚀 Essential Learning Resources
Top 3 Courses (Free)
- Maxime Labonne's LLM Course - 20+ Colab notebooks
- Maps to JD: "Experience in Large Language Model (LLM) tuning" + "Model evaluation, validation, and performance metrics, particularly for LLMs"
- DeepLearning.AI LangChain Course - 1 hour, practical
- Maps to JD: "Experience in developing AI agents for automating decision-making" + "Drive end-to-end machine learning workflows"