Advanced DeepSeek: Fine-Tuning, Optimization, and Deployment

סקירה כללית

In the rapidly advancing field of AI, fine-tuning, optimizing, and deploying models like DeepSeek are essential for building specialized, scalable systems. This course covers the most advanced techniques in AI model development, focusing on DeepSeek's adaptation for domain-specific applications such as legal reasoning, performance optimization, and deployment strategies.

Through in-depth lessons, learners will explore the fine-tuning process for improving model accuracy, optimizing performance, and deploying DeepSeek models in production environments. You will delve into topics like model distillation, cloud-based deployment strategies, and cost management, enabling you to scale AI systems effectively while ensuring performance meets real-world needs.

What makes this course stand out is its practical focus on deployment scenarios and optimization strategies that help learners apply their knowledge directly to the challenges they will encounter in professional settings. You'll gain the expertise to make strategic decisions regarding deployment frameworks, hardware, and production operations, making your AI models not only efficient but also sustainable in long-term applications.

This course is ideal for AI practitioners, engineers, and data scientists with experience in machine learning or deep learning. It requires familiarity with machine learning concepts and AI deployment practices.

This course is part three of a three-course Specialization designed to provide a comprehensive learning pathway in this subject area. While it delivers standalone value and practical skills, learners seeking a more integrated and in-depth progression may benefit from completing the full Specialization.

סילבוס

• DeepSeek-Driven Fine-Tuning of Gemma 3 for Legal Reasoning
This module guides learners through the process of fine-tuning large language models for legal reasoning, focusing on distillation techniques, multi-label extraction in legal texts, and the use of LLMOps tools for reproducible workflows. Learners will gain hands-on experience with data processing pipelines, model evaluation, and performance optimization strategies tailored to legal AI applications.
• Deploying DeepSeek Models
This module guides learners through the practical steps and strategic decisions involved in deploying DeepSeek models, from hardware selection and cost analysis to hands-on deployment on various platforms. Learners will explore deployment strategies, optimization techniques like quantization, and best practices for production operations, monitoring, and cost management. By the end, participants will be equipped to choose and implement the most suitable deployment path for their needs.

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נלמד על ידי

Packt - Course Instructors

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נושאים

Artificial Intelligence