You will work with Python, Hugging Face Transformers, and commonly used machine learning libraries to build practical fine-tuning workflows.

Yes. The course introduces LoRA and PEFT, explaining how they reduce training costs while maintaining strong model performance.

You will use evaluation metrics such as Accuracy, F1 Score, BLEU, ROUGE, and Perplexity, along with error analysis techniques to assess model quality.

Yes. You will explore hyperparameter tuning, learning rate scheduling, gradient accumulation, and other optimization techniques that improve fine-tuning results.

Yes. The concepts and techniques covered in this course are directly applicable to fine-tuning modern large language models for domain-specific applications.

Yes. After successfully completing all course requirements, you will receive a certificate that you can share with employers and on professional platforms.

Unlike traditional machine learning courses, this course focuses specifically on adapting pretrained AI models using modern fine-tuning techniques, efficient training methods, and production-ready evaluation workflows.

To access course materials, assignments, and earn a Certificate, you'll need to purchase the Certificate experience when you enroll in a course. Eligible learners may also have the option to start with a Free Trial. Some courses may also offer a Full Course, No Certificate option. This lets you access course materials, submit required assessments, and receive a final grade, but you won't be able to earn or purchase a Certificate.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.