LLM
Career Objective
COURSE OBJECTIVE:Â
Understand the Basics of Large Language Models: Gain a foundational understanding of what large language models are and how they work.
- Explore Natural Language Understanding (NLU):Learn how large language models process and interpret natural language input.
- Master Natural Language Generation (NLG):Explore methods for generating human-like text and coherent responses.
Course Instructions
- Follow the course sequence to qualify for the complete course certificate.
- Each module completed individually earns a certificate specific to that module.
- Completing the entire sequence is necessary to obtain the full course certificate.
- Sequential completion ensures thorough learning and mastery.
- Each module certificate acknowledges acquisition of specific skills.
- To earn the full course certificate, completing all modules in sequence is mandatory.
- Following the correct sequence enhances comprehension and application.
- Certificates for individual modules recognize targeted skill advancement.
What you will learn?
- Â Gain a comprehensive understanding of what large language models are and how they function.
Explore the architecture, components, and training methodologies of state-of-the-art models like GPT-3.
Learn how large language models process and generate human-like text.
- Understand tokenization, attention mechanisms, and transformer architectures used in NLP tasks.
- Learn how to evaluate the performance and quality of generated text.
Explore metrics for assessing language model proficiency, coherence, and grammaticality.
- Apply your knowledge through hands-on projects and exercises that involve implementing and experimenting with large language models.
- Develop skills in model deployment, integration with APIs, and real-world application development.
MODULE SEQUENCE TO BE FOLLOWED:
This course includes:
- 40 hours on-demand videos
- Interesting Quizes for every module
- Individual certificates
- Provide Badges
- App Accessissibility
- Full Time Access
- Feedback Mechanism
- Downloadable Materials
- Resource Library
Frequently Asked Questions
This course is ideal for data scientists, machine learning engineers, software developers, researchers, and anyone interested in understanding and applying large language models.
 Basic knowledge of machine learning concepts, proficiency in Python programming, and familiarity with natural language processing (NLP) fundamentals (e.g., tokenization, word embeddings) are recommended.
  The course is structured into modules covering foundational concepts of large language models, natural language understanding (NLU), natural language generation (NLG), applications across different domains, hands-on coding exercises, advanced topics, ethical considerations, and practical projects.
Yes, upon successfully completing the course and projects, you will receive a certificate of achievement. This certificate validates your proficiency in large language models and practical skills in applying them to real-world tasks.
This course will prepare you for roles such as NLP engineer, AI researcher, data scientist specializing in NLP, or software developer working with language generation technologies.
  Yes, you will have access to instructor support through forums, office hours, or discussion boards to address any questions or challenges you encounter during the course.
