Certified LLM Developer™

In today’s world of advanced artificial intelligence, large language models (LLMs) are reshaping technology and driving innovation forward. The Certified LLM Developer Certification program is crafted to provide you with the comprehensive skills and knowledge needed to develop, fine-tune, and deploy LLMs. This program offers a deep dive into LLM architectures, tools, and best practices, coupled with hands-on experience in building AI models capable of understanding and generating human-like text. Through immersive learning, you’ll gain the expertise to create intelligent, context-aware applications that push the boundaries of AI solutions. Become a Certified LLM Developer and lead the way in developing cutting-edge AI-driven language models. Be at the forefront of a world where LLMs revolutionize communication, decision-making, and innovation, with your skills driving technological progress. Join us and shape the future of AI.

$299

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Course duration

13 Hours

Exam

Self-paced

Access Mode

Online

Certification Validity

Lifetime

Modules Included

  • LLM Overview
  • Evolution of LLMs
  • Capabilities and Limitations of LLMs
  • Applications and use cases of LLMs
  • Tokenization, Vectors and Embeddings
  • Attention Mechanism and its variants
  • Introduction to Transformer Architecture
  • Creating Custom Language Models
  • Transfer Learning in NLP
  • Evaluation Metrics for LLMs: BLEU, ROUGE, Perplexity
  • Introduction to Hugging Face Transformers library
  • Overview of llama2 and Gemma
  • Fine Tuning Gemma Model
  • Overview of popular LLMs: GPT-3/4, BERT, T5
  • Fine-tuning pre-trained models for specific tasks
  • BERT and its variants: RoBERTa, DistilBERT
  • GPT and its applications in text generation
  • Exploring other models: T5, XLNet, ELECTRA
  • Building conversational agents and chatbots
  • Creative applications: text generation, storytelling
  • Ethical considerations and bias mitigation in LLMs
 
  • Understanding Computer Vision
  • CNN from Scratch
  • CNN using Tensorflow
  • Basics of audio signal processing
  • Feature extraction: MFCCs, Spectrograms
  • Audio classification and speech recognition
  • Basics of video signal processing
  • Frame extraction and video feature analysis analysis
  • LangChain – Langchain for Conversational AI Applications
  • LangChain – Deploying Language Model APIs with Langchain
  • LangChain – Langchain for RAG Workflows
  • Ollama – Overview of Ollama for conversational AI
  • Ollama – Developing and deploying conversational agents with Ollama
  • Overview of Text Classification Model
  • Bert text classification
  • Data preparation and preprocessing
  • Text Generation Model
  • Overview of Text Generation Model
  • Evaluation and fine-tuning
  • Evaluation and fine-tuning
 
  • Overview of Designing a conversational agent architecture
  • Conversational Agent
  • Conversational agent using openAI
  • Conversational Agent using LangChain
  • Conversational Agent using Ollama
  • Conversational Agent using HuggingFace
 
  • Deploying LLMs with Flask and FastAPI
  • Introduction to Docker for containerization
  • Deploying LLMs on cloud platforms (AWS)
  • Introduction to MLOps concepts and practices
  • Continuous Integration and Continuous Deployment
  • Monitoring model performance in production
  • There will be an online training followed by a multiple choice exam of 100 marks.
  • You need to acquire 60+ marks to clear the exam.
  • If you fail, you can retake the exam after one day.
  • You can take the exam no more than 3 times.
  • If you fail to acquire 60+ marks even after three attempts, then you need to contact us to get assistance for clearing the exam

Top Job Roles

A Certified LLM Developer is a recognized expert whose certification demonstrates exceptional proficiency in large language models. These professionals have in-depth skills and knowledge in developing, fine-tuning, and deploying LLMs, allowing them to create advanced AI-driven solutions. As innovators in the field, they apply their expertise to build intelligent applications capable of understanding and generating human-like text across diverse domains. Certified LLM Developers play a crucial role in expanding the potential of AI language models, driving the development of cutting-edge applications and solutions across various industries.

This certification program is perfect for those with a passion for artificial intelligence, natural language processing, and language models. It is tailored for software developers, data scientists, AI researchers, and anyone looking to pursue a career in AI-driven language modeling. Whether you are an experienced professional aiming to expand your expertise or a newcomer to the field, this certification equips you with the knowledge and skills needed to thrive in the fast-evolving world of large language models.

Certified LLM Developers specialize in developing, fine-tuning, and deploying large language models to create intelligent, context-aware applications. They leverage their expertise in LLM architectures, tools, and techniques to build AI models capable of understanding, generating, and engaging with human language in meaningful ways. These professionals collaborate with cross-functional teams to integrate LLM-driven solutions into various applications, such as chatbots, virtual assistants, content generation tools, and automated decision-making systems. Their role is essential in ensuring the technical and functional excellence of AI-powered language models, driving innovation and efficiency across diverse industries.

Technology and SaaS, healthcare and agritech, as well as e-commerce and finance.

Certification Benefits

Frequently Asked Questions

A Certified LLM Developer is a certified professional with specialized expertise in developing, fine-tuning, and deploying large language models. Their certification serves as proof of their advanced knowledge and skills in the field, validating their proficiency in LLM development.

The certification is ideal for software developers, data scientists, AI researchers, and anyone looking to pursue a career in AI-driven language modeling.

The benefits include a comprehensive understanding of LLM development, validation of expertise, opportunities for career growth, industry recognition, and access to continuous learning and networking opportunities.

Yes, you can retake the certification exam if you don’t pass the first time. Please review the certification guidelines for detailed information on retake policies and procedures.

There are no formal prerequisites for enrolling in the Certified LLM Developer program. However, having a basic understanding of programming, AI concepts, and natural language processing can be helpful.

The Certified LLM Developer program offers a flexible learning schedule, allowing you to progress at your own pace. Although the recommended completion time is six weeks, the actual duration may vary depending on your individual learning style and prior experience.

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