Description

AI Reasoning Models: The Building Blocks for the Next Generation of AI Applications. This course is a comprehensive program that examines reasoning models in artificial intelligence and how they can be built and used to solve complex problems. This course examines a new class of large language models that have enhanced reasoning capabilities, known as reasoning models. This course explains the key differences between these emerging models and traditional large language models and explains why they are so effective in solving complex challenges, including solving programming problems, puzzles, and advanced problem-solving domains. Along the way, students will learn how these advanced tools can improve the performance of intelligent systems when faced with complex data and situations. Throughout the course, three main approaches to building and enhancing reasoning capabilities in large language models are presented, using real-world case studies such as the DeepSeek-R1 model. Participants gain valuable hands-on experience in the areas of scalability during inference, reinforcement learning, and knowledge distillation. The trade-off between quality performance, efficiency, and development costs when using reasoning models compared to traditional models is also thoroughly analyzed. The course is integrated with Codespaces’ GitHub environment, which provides a real-time cloud development environment and allows for hands-on practice without the need for local configuration. By the end, learners will be fully prepared to implement and use reasoning models in their next projects.

What you will learn

• Understanding the key differences between traditional large language models and AI reasoning models
• Introduction to the three main methods of building and enhancing reasoning capabilities in language models through the DeepSeek-R1 case study
• Gain practical experience in inference-time scalability, machine learning, and knowledge distillation methods
• Analysis and evaluation of development costs, efficiency, and qualitative performance of reasoning models compared to conventional models
• Using Codespaces’ GitHub cloud environment to develop and run AI projects without the need for local setup

This course is suitable for people who:

• AI developers and engineers who want to use the next generation of reasoning models in their applications
• Researchers and enthusiasts in the field of productive artificial intelligence who seek a deeper understanding of advanced problem-solving methods
• Professionals who face complex programming and computing challenges and need smarter tools
• People who want to improve their practical skills in the field of Ta’zizi learning and large language models

Course specifications AI Reasoning Models: The Building Blocks for the Next Generation of AI Applications

• Publisher: LinkedIn
• Instructor: Sebastian Raschka
• Training level: Advanced
• Training duration: 1 hour and 32 minutes

Course topics

Course images

Sample course video

Download link

Download file – 300 MB

Rapidgator link

Download File – 300 MB

File(s) password: www.downloadly.ir

File size

300 MB