20 hrs
Cohere LLM University is a free, hands-on course from Cohere—one of the leading AI companies behind production language models used globally. This course teaches you the core techniques that power modern AI: text embeddings (understanding meaning), classification (categorizing text), generation (creating text), and RAG (retrieval-augmented generation, which lets AI pull from real data). Whether you're building an AI product or trying to understand how these systems work under the hood, this course bridges the gap between theory and practice.
This course is for anyone who wants to move beyond "playing with ChatGPT" and actually understand how to build with language models. You don't need to be a machine learning expert—just curious and willing to get hands-on.
Basic familiarity with Python is helpful. You should be comfortable with concepts like functions and data structures. No machine learning background needed—the course assumes you're starting fresh on the AI side.
India's AI job market is exploding. Companies across fintech, e-commerce, healthcare tech, and SaaS are building AI features—from Razorpay's fraud detection to Flipkart's search and recommendations to health-tech startups using AI for diagnostics. Learning embeddings, classification, and RAG makes you immediately valuable for these roles, and many pay ₹8–15 lakh annually for mid-level AI engineers. Cohere's tools are free and production-grade, so what you learn here translates directly to what companies actually use.
Yes. Cohere offers this course completely free—no hidden paywall, no paid certificate upsell. You can take it at your own pace.
The course is designed as a 20-hour commitment. If you dedicate 3–4 hours per week, you'll finish in 5–6 weeks. You can go faster or slower depending on how deeply you want to practice.
This course does not offer a certificate of completion. However, the real credential is the skills you build—use what you learn to build a small project (a classifier, a RAG chatbot, or a search feature) and that becomes your portfolio proof.