What You'll Learn
- Design and engineer effective prompts using proven frameworks like Chain-of-Thought, Step-Back, and Role prompting.
- Tune and control LLM behavior by adjusting hyperparameters such as temperature, top-p, max tokens, and penalties.
- Run and customize Large Language Models locally using Ollama and integrate them with Python applications.
- Build complete Generative AI workflows using LangChain, including prompt templates, chains, memory, and dynamic routing.
- Develop Retrieval-Augmented Generation (RAG) systems that combine LLMs with vector databases for grounded, factual answers.
- Design user-friendly AI interfaces using Streamlit and explore On-Device AI deployment with Qualcomm AI Hub.
Requirements
- No prior AI or coding experience required—just a curious mindset, basic computer skills, and a PC with internet access.
Who This Course is For
- Beginners and tech enthusiasts who want to understand and build real-world Generative AI applications from scratch.
- Developers, data scientists, and AI learners eager to master prompt engineering, LangChain, and Retrieval-Augmented Generation (RAG).
- AI professionals and product managers aiming to run, customize, and deploy LLMs locally or on-device for performance and privacy.
- Python programmers and innovators looking to create interactive GenAI apps using LangChain, Streamlit, and Qualcomm AI Hub.
- Students and researchers interested in exploring how Large Language Models work under the hood and how to fine-tune their behavior.
Your Instructor
Start-Tech Academy
5,000,000+ Enrollments | 4.5 Rated | 160+ Countries
4.5 Instructor Rating
167,512 Reviews
2,060,290 Students
135 Courses
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