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Evaluation Ops (LLM/Workflow Regression Testing)
Original price was: INR ₹11,000.00.INR ₹5,499.00Current price is: INR ₹5,499.00.
Evaluation Ops (LLM/Workflow Regression Testing) is a Intermediate-level, 4 Weeks online program by NSTC. Master Artificial Intelligence, Evaluation, LLM through hands-on projects, real datasets, and expert mentorship.
Earn your e-Certification + e-Marksheet in evaluation ops (llm/workflow regression testing). Designed for NLP engineers, computational linguists, chatbot developers, and data scientists seeking practical nlp expertise in India.
About the Course
Evaluation Ops (LLM/Workflow Regression Testing) dives deep into Evaluation Ops (Llm/Workflow Regression Testing). Gain comprehensive expertise through our structured curriculum and hands-on approach.
Course Curriculum
NLP Foundations, Linguistics, and Evaluation Ops (Llm/Workflow Regression Testing) Fundamentals
- Implement Artificial Intelligence with Evaluation for practical nlp foundations, linguistics, and evaluation ops (llm/workflow regression testing) fundamentals applications and outcomes.
- Design LLM with Ops for practical nlp foundations, linguistics, and evaluation ops (llm/workflow regression testing) fundamentals applications and outcomes.
- Analyze tokenization with language models for practical nlp foundations, linguistics, and evaluation ops (llm/workflow regression testing) fundamentals applications and outcomes.
Text Preprocessing, Tokenization, and Feature Engineering
- Implement Artificial Intelligence with Evaluation for practical text preprocessing, tokenization, and feature engineering applications and outcomes.
- Design LLM with Ops for practical text preprocessing, tokenization, and feature engineering applications and outcomes.
- Analyze tokenization with language models for practical text preprocessing, tokenization, and feature engineering applications and outcomes.
Classical NLP Models and Statistical Methods
- Implement Artificial Intelligence with Evaluation for practical classical nlp models and statistical methods applications and outcomes.
- Design LLM with Ops for practical classical nlp models and statistical methods applications and outcomes.
- Analyze tokenization with language models for practical classical nlp models and statistical methods applications and outcomes.
Deep Learning Architectures for Evaluation Ops (Llm/Workflow Regression Testing)
- Implement Artificial Intelligence with Evaluation for practical deep learning architectures for evaluation ops (llm/workflow regression testing) applications and outcomes.
- Design LLM with Ops for practical deep learning architectures for evaluation ops (llm/workflow regression testing) applications and outcomes.
- Analyze tokenization with language models for practical deep learning architectures for evaluation ops (llm/workflow regression testing) applications and outcomes.
Transformers, LLMs, and Attention Mechanisms
- Implement Artificial Intelligence with Evaluation for practical transformers, llms, and attention mechanisms applications and outcomes.
- Design LLM with Ops for practical transformers, llms, and attention mechanisms applications and outcomes. Gain hands-on experience and produce real-world projects.
- Analyze tokenization with language models for practical transformers, llms, and attention mechanisms applications and outcomes.
Model Evaluation, Fine-Tuning, and Optimization
- Implement Artificial Intelligence with Evaluation for practical model evaluation, fine-tuning, and optimization applications and outcomes.
- Design LLM with Ops for practical model evaluation, fine-tuning, and optimization applications and outcomes. Gain hands-on experience and produce real-world projects.
- Analyze tokenization with language models for practical model evaluation, fine-tuning, and optimization applications and outcomes.
Production NLP Systems, APIs, and Deployment
- Implement Artificial Intelligence with Evaluation for practical production nlp systems, apis, and deployment applications and outcomes.
- Design LLM with Ops for practical production nlp systems, apis, and deployment applications and outcomes.
- Analyze tokenization with language models for practical production nlp systems, apis, and deployment applications and outcomes.
Domain-Specific Applications and Real-World Evaluation Ops (Llm/Workflow Regression Testing) Solutions
- Implement Artificial Intelligence with Evaluation for practical domain-specific applications and real-world evaluation ops (llm/workflow regression testing) solutions applications and outcomes.
- Design LLM with Ops for practical domain-specific applications and real-world evaluation ops (llm/workflow regression testing) solutions applications and outcomes.
- Analyze tokenization with language models for practical domain-specific applications and real-world evaluation ops (llm/workflow regression testing) solutions applications and outcomes.
Capstone: End-to-End Evaluation Ops (Llm/Workflow Regression Testing) NLP Pipeline
- Implement Artificial Intelligence with Evaluation for practical capstone: end-to-end evaluation ops (llm/workflow regression testing) nlp pipeline applications and outcomes.
- Design LLM with Ops for practical capstone: end-to-end evaluation ops (llm/workflow regression testing) nlp pipeline applications and outcomes.
- Analyze tokenization with language models for practical capstone: end-to-end evaluation ops (llm/workflow regression testing) nlp pipeline applications and outcomes.
Real-World Applications
- Apply Artificial Intelligence to voice assistants for impactful real-world solutions and tangible results.
- Apply Evaluation to text analytics for impactful real-world solutions and tangible results.
- Apply LLM to sentiment analysis for impactful real-world solutions and tangible results.
- Apply Ops to search engines for impactful real-world solutions and tangible results.
- Apply Artificial Intelligence to chatbots for impactful real-world solutions and tangible results.
Tools, Techniques, or Platforms Covered
Artificial Intelligence
Who Should Attend & Prerequisites
- Designed for NLP engineers.
- Designed for Computational linguists.
- Designed for Data scientists.
- Designed for Chatbot developers.
- Foundational knowledge of nlp and familiarity with core concepts recommended.
Program Highlights
- Mentorship by industry experts and NSTC faculty.
- Hands-on projects using Artificial Intelligence.
- Case studies on emerging nlp innovations and trends.
- e-Certification + e-Marksheet upon successful completion.
Frequently Asked Questions
1. What is the Evaluation Ops (LLM/Workflow Regression Testing) Course by NSTC?
The Evaluation Ops (LLM/Workflow Regression Testing) Course by NSTC is a practical, hands-on program that teaches how to systematically evaluate, test, and maintain the quality of Large Language Models (LLMs) and complex AI workflows. You will learn regression testing strategies, automated evaluation frameworks, performance benchmarking, hallucination detection, prompt testing, output validation, and continuous monitoring using tools like Hugging Face, Python, NLTK, spaCy, and custom evaluation pipelines.
2. Is the Evaluation Ops (LLM/Workflow Regression Testing) course suitable for beginners?
Yes, the NSTC Evaluation Ops course is suitable for beginners who have basic Python and NLP/LLM knowledge. The course starts with foundational evaluation concepts and gradually advances to advanced regression testing and automated quality assurance for LLMs and AI workflows, with clear step-by-step guidance and practical examples.
3. Why should I learn the Evaluation Ops (LLM/Workflow Regression Testing) course in 2026?
In 2026, LLMs and generative AI are being deployed widely, but without proper evaluation and regression testing, models can degrade, produce hallucinations, or fail silently. This NSTC course equips you with essential skills to ensure reliability, consistency, and safety of AI systems, which is now a critical requirement for production-grade LLM applications in enterprises.
4. What are the career benefits and job opportunities after the Evaluation Ops course?
This course prepares you for high-demand roles such as LLM Evaluation Engineer, AI Quality Assurance Specialist, MLOps Evaluation Lead, Prompt Evaluation Analyst, and Generative AI Testing Engineer. In India, professionals skilled in LLM/Workflow evaluation and regression testing can expect salaries ranging from ₹12–28 lakhs per annum, with strong demand in AI product companies, fintech, healthcare, and enterprises building production LLMs.
5. What tools and technologies will I learn in the NSTC Evaluation Ops (LLM/Workflow Regression Testing) course?
You will master Python for evaluation automation, Hugging Face for model testing, custom metrics for sentiment analysis, text classification, named entity recognition, hallucination detection, regression testing frameworks, automated benchmarking, prompt evaluation techniques, and tools for continuous monitoring of LLM workflows.
6. How does NSTC’s Evaluation Ops course compare to Coursera, Udemy, or other Indian courses?
Unlike general LLM or NLP courses on Coursera, Udemy, or edX that focus mainly on building models, NSTC’s Evaluation Ops (LLM/Workflow Regression Testing) course is specifically focused on quality assurance, regression testing, and evaluation frameworks for production LLMs. It provides deeper practical training with real use cases, model demos, and benchmark comparisons, making it more job-ready for AI evaluation roles.
7. What is the duration and format of the NSTC Evaluation Ops online course?
The Evaluation Ops (LLM/Workflow Regression Testing) course is a flexible 3-week online program in a modular format, ideal for working professionals and students across India. It combines conceptual lessons with extensive hands-on coding, evaluation pipeline building, and real LLM testing projects.
8. What certificate will I receive after completing the NSTC Evaluation Ops course?
Upon successful completion, you will receive a valuable e-Certification and e-Marksheet from NanoSchool (NSTC). This industry-recognized certificate validates your expertise in Evaluation Ops for LLMs and AI workflows and can be proudly added to your LinkedIn profile and resume, strengthening your profile in the rapidly growing generative AI quality assurance domain.
9. Does the Evaluation Ops (LLM/Workflow Regression Testing) course include hands-on projects for building a portfolio?
Yes, the course includes several hands-on projects such as building automated regression testing pipelines for LLMs, creating evaluation benchmarks for text generation, implementing hallucination detection systems, developing continuous monitoring dashboards for workflows, and performing prompt regression testing. These practical projects help you build a strong portfolio showcasing your ability to ensure quality in production LLM systems.
10. Is the Evaluation Ops (LLM/Workflow Regression Testing) course difficult to learn?
The NSTC Evaluation Ops course is challenging but very practical and well-supported. With clear explanations, code examples, model demos, and progressive modules focused on real LLM evaluation scenarios, even those new to advanced testing concepts can confidently master the techniques. The course is designed to build your expertise progressively for production AI quality assurance.
| Brand | NSTC |
|---|---|
| Format | Online (e-LMS) |
| Duration | 3 Weeks |
| Level | Advanced |
| Domain | AI, Data Science, Automation, Artificial Intelligence |
| Hands-On | Yes – Practical projects with industrial datasets |
| Tools Used | Python, TensorFlow, Power BI, MLflow, ML Frameworks, Computer Vision |
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