Who should enroll in this LLMs and Generative AI course?

This course is suitable for AI learners, data science students, machine learning professionals, software developers, researchers, PhD scholars, academicians, business professionals, digital content creators, NLP learners, and professionals interested in generative AI applications.

Does this course cover prompt engineering and NLP applications?

Yes. The course covers prompt engineering, natural language processing concepts, LLM workflows, text generation, AI-assisted content creation, model interaction strategies, and practical ways to use generative AI tools effectively.

Will learners understand practical applications of large language models?

Yes. Learners explore practical LLM applications such as question answering, summarization, content generation, research assistance, automation, chatbot workflows, AI productivity tools, and responsible generative AI use.

Is this course useful for AI, research, and professional technology careers?

Yes. The course helps learners build practical knowledge of large language models, generative AI, NLP, prompt engineering, AI workflows, and responsible AI applications useful for AI careers, research, software development, business innovation, education technology, and data-driven roles.

Large Language Models (LLMs) And Generative AI

Q: What is the Large Language Models (LLMs) and Generative AI course about?

This course teaches large language models, generative AI, natural language processing, prompt engineering, AI-powered content generation, and practical applications of LLMs in research, business, education, and technology.

Attribute

Detail

Format

Recorded Lectures (Self-Paced)

Level

Intermediate

Duration

3 Days

Certification

e-Certification + e-Marksheet

Tools

Python, NLTK, spaCy, Hugging Face Transformers, Gensim, BERT

About the Large Language Models (Llms) And Generative Ai Course

This course focuses on the fundamentals, advanced techniques, and real-world applications of Large Language Models (LLMs) and Generative AI.

Participants will learn about state-of-the-art technologies like GPT, Transformers, and Diffusion Models. The program emphasizes hands-on training, enabling participants to create AI-driven solutions for text generation, creative content, chatbots, and more.

Program Highlights

• Comprehensive coverage of Large Language Models (LLMs) and Generative AI from fundamentals to advanced applications

• Hands-on projects and real-world case studies in Natural Language Processing

• Expert-curated curriculum aligned with current industry standards

• Access to recorded lectures and e-LMS platform for flexible, self-paced learning

• e-Certification and e-Marksheet upon successful completion

• Dedicated mentor support and interactive doubt-clearing sessions

• Exposure to industry-standard tools and platforms used in Natural Language Processing

• Career-oriented training for academic and professional growth in Natural Language Processing

Course Curriculum

Module 1: Introduction to Large Language Models (LLMs) and Generative AI

Overview and historical evolution of Large Language Models (LLMs) and Generative AI
Key terminology, definitions, and core concepts in Natural Language Processing
Current industry landscape, trends, and career opportunities
Setting up the learning environment and essential tools

Module 2: Fundamentals and Theoretical Foundations

Core principles and scientific/theoretical underpinnings of Large Language Models (LLMs) and Generative AI
Mathematical and analytical frameworks relevant to Natural Language Processing
Comparative analysis of major approaches and methodologies
Understanding key standards, guidelines, and best practices

Module 3: Text Processing

Introduction to Text Processing concepts and methodologies
Step-by-step practical implementation of Text Processing techniques
Tools and platforms commonly used for Text Processing
Troubleshooting, optimization, and best practices

Module 4: Sentiment Analysis

Introduction to Sentiment Analysis concepts and methodologies
Step-by-step practical implementation of Sentiment Analysis techniques
Tools and platforms commonly used for Sentiment Analysis
Troubleshooting, optimization, and best practices

Module 5: Named Entity Recognition

Introduction to Named Entity Recognition concepts and methodologies
Step-by-step practical implementation of Named Entity Recognition techniques
Tools and platforms commonly used for Named Entity Recognition
Troubleshooting, optimization, and best practices

Module 6: Advanced Topics and Emerging Trends in Natural Language Processing

Cutting-edge research and innovations in Large Language Models (LLMs) and Generative AI
Integration with AI, automation, and modern technologies
Industry case studies and real-world problem solving
Future directions and career pathways in Natural Language Processing

Module 7: Capstone Project and Assessment

End-to-end project implementation using Large Language Models (LLMs) and Generative AI skills
Peer review, collaborative exercises, and expert feedback
Portfolio-ready project documentation and presentation
Final assessment and course completion evaluation

Tools, Techniques, or Platforms Covered

Python
NLTK
spaCy
Hugging Face Transformers
Gensim
BERT
GPT

Real-World Applications

Apply Large Language Models (LLMs) and Generative AI skills directly to academic research, thesis work, and publications
Build a professional portfolio showcasing practical Natural Language Processing competencies
Solve industry-relevant problems using Large Language Models (LLMs) and Generative AI methodologies and tools
Contribute to open-source projects and collaborative research in Natural Language Processing
Prepare for competitive examinations, interviews, and professional certifications in Natural Language Processing

Who Should Attend & Prerequisites

Students pursuing degrees in Natural Language Processing, science, engineering, or related disciplines
Working professionals seeking to upskill or transition into Natural Language Processing roles
Researchers and academicians looking to adopt modern techniques in Natural Language Processing
Entrepreneurs, freelancers, and self-learners interested in practical Natural Language Processing knowledge

Prerequisites: Some familiarity with basic concepts in Natural Language Processing will be helpful but is not mandatory. A willingness to learn and engage with hands-on exercises is essential.

Frequently Asked Questions

1. What is the format of this Large Language Models (LLMs) and Generative AI course?

This is an Recorded Lectures (Self-Paced) course delivered via our e-LMS platform. You will have access to pre-recorded video lectures, reading materials, assignments, quizzes, and hands-on projects that you can complete at your own pace.

2. Will I receive a certificate after completing this course?

Yes! Upon successful completion of all modules, assignments, and assessments, you will receive an e-Certification along with an e-Marksheet from NanoSchool (NSTC) that you can showcase on your CV and LinkedIn profile.

3. What are the prerequisites for this course?

Learners should have a foundational understanding of Natural Language Processing concepts. Familiarity with basic tools and programming is recommended.

4. How long will I have access to the course materials?

You will have access to all course materials for the duration of 3 Days. The self-paced format allows you to learn according to your own schedule through our online learning management system.

5. Is mentor support available during the course?

Yes, dedicated mentor support is available throughout the course. You can reach out for doubt-clearing sessions, project guidance, and career advice related to Natural Language Processing. Our mentors are industry experts and experienced professionals.

Enroll in Large Language Models (LLMs) and Generative AI today and take the next step in your professional journey. With expert-curated content, practical projects, and industry-recognized certification, this course is your gateway to mastering Natural Language Processing skills that matter.

Brand	NSTC
Format	Recorded Lectures
Duration	3 Days
Level	Intermediate
Hands-On	Yes – Practical projects with industrial datasets

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Large Language Models (LLMs) and Generative AI