AI Engineering for Data Scientists – Training and Fine-Tuning Large Models with 10 Exams
Behind each tutorial is human creativity, AI support and the careful oversight of human editors. Build the skills to shape AI systems for real-world impact. As AI grows, so does the need to manage and adapt large-scale models.
This course includes.
Curriculum & lectures.
+ 01 AI Engineering Foundations & The Rise of LLMs 8 lectures Preview
+ 02 Data Foundations for Training & Fine-Tuning 9 lectures
+ 03 Fine-Tuning Strategies & Adaptation 4 lectures
+ 04 Evaluation, Deployment, and Scaling 10 lectures
+ 05 Security, Governance & The Future of AI Engineering 5 lectures
About this course.
This course explores how data scientists can train, fine-tune, and evaluate models, focusing on methods that make AI systems more efficient and aligned with specific tasks.
✅ Train and adapt models for specialized applications
✅ Explore techniques for fine-tuning large architectures
✅ Learn evaluation methods to measure performance
✅ Reinforce learning with 10 structured exams
AI engineering combines experimentation with systematic refinement, helping turn cutting-edge models into tools for practical use.
🎁 Build the skills to shape AI systems for real-world impact.
Bundled items.
10 courses
Ready to start building?
Behind each tutorial is human creativity, AI support and the careful oversight of human editors. Build the skills to shape AI systems for real-world impact. As AI grows, so does the need to manage and adapt large-scale models.