About This Course
Welcome to the "From Beginner to Advanced LLM Developer" course offered by the PSDC in collaboration with Towards AI Academy. This comprehensive program is designed for developers, engineers, and anyone interested in mastering the art and science of Large Language Models (LLMs). Whether you're at the beginning of your journey into AI or looking to deepen your expertise, this course provides the roadmap to transform you into a professional LLM developer.
In an era where LLMs are pivotal in driving innovation across industries, from enhancing customer service through chatbots to revolutionizing content creation, this course is your gateway to understanding, building, and deploying these sophisticated AI models. You'll start with the fundamentals, progressing through advanced techniques, and gain hands-on experience that aligns with real-world application.
Learning Objectives
Upon completing this course, you will be able to:
- Understand the fundamental concepts of Large Language Models (LLMs), including prompt engineering, retrieval-augmented generation (RAG), and fine-tuning techniques.
- Develop and integrate LLM-powered applications using APIs, vector databases, and indexing strategies to optimize retrieval performance.
- Implement and evaluate advanced RAG techniques, including chunking, embedding models, and metadata filtering, to enhance information retrieval accuracy.
- Deploy LLM-based applications with user-friendly interfaces using Gradio and cloud platforms like Hugging Face Spaces.
- Expand their AI toolkit by exploring various frameworks such as LangChain, OpenAI Assistants, and agent-based pipelines for complex task automation.
- Comprehend market trends and monetization opportunities within the LLM ecosystem to develop strategic and competitive AI-driven business solutions.
- Certification: Earn a certification upon course completion, validating your expertise in LLM development, which can be a significant asset in your career advancement or transition into AI role
Prerequisites
- Basic Python Programming: Understanding of Python is essential, though the course includes a primer for those with less experience.
- Fundamental AI Concepts: A general grasp of AI and machine learning concepts is helpful, though not mandatory as foundational lessons are included.
- Interest in AI Development: A keen interest in learning and applying AI technologies, particularly LLMs.
- Problem-Solving Skills: Ability to think critically about how to apply LLMs to solve real- world problems.
Target Audience
- Developers and Engineers looking to specialize in AI, particularly with LLMs.
- Practitioner aiming to expand their toolkit with LLM development skills for enhanced data analysis and AI product development.
- Entrepreneurs and Innovators: Seeking to integrate AI into their business models or products.
- Students: Interested in AI and looking to prepare for a career in LLM development or related fields.
Training Outline
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Understanding LLMs & Course Introduction
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LLMs Prompt Engineering, Retrieval-Augmented Generation (RAG), Tools, Fine- Tuning
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RAG Fundamentals Developing an OpenAI-powered Chatbot
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LlamaIndex & Vector Databases Data Collection, Filtering, and Cleaning
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Advanced RAG Techniques Chunking, Indexing, and Embedding Models
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Deploying LLM Applications Building a Gradio UI and Hosting on Hugging Face
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Exploring More LLM Frameworks & Tools Expanding Your AI Toolkit
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LLM Optimization Improving Model Efficiency
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LLM Ecosystem & Business Strategy Market Trends & Monetization Opportunities