Certified LLM Developer™

In the era of advanced artificial intelligence, large language models (LLMs) are transforming the landscape of technology and innovation. The Certified LLM Developer Certification program is meticulously designed to equip you with the comprehensive knowledge and cutting-edge skills needed to develop, fine-tune, and deploy large language models. This program offers an in-depth understanding of LLM architectures, tools, and best practices, providing hands-on experience in building AI models that can understand and generate human-like text. Through immersive learning experiences, you’ll master the art of working with LLMs to create intelligent, context-aware applications that push the boundaries of AI-driven solutions. Join us and emerge as a Certified LLM Developer™, ready to lead the field in developing sophisticated AI-driven language models. Be at the forefront of a world where language models enhance communication, decision-making, and innovation, and your expertise becomes a key driver of technological advancement.

₹23,999

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Course Duration

13 Hours

Online

Exam

Self-paced

Access Mode

Lifetime

Validity & Access

Modules Included

Introduction to Large Language Models

LLM Overview
Evolution of LLMs
Capabilities and Limitations of LLMs
Applications and use cases of LLMs

Core LLM Technologies

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

Advanced LLM Techniques

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

Computer Vision

Understanding Computer Vision
CNN from Scratch
CNN using Tensorflow

Audio/Video Coding

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

LLM Frameworks and Tools

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

Project 1: Text Classification Model

Overview of Text Classification Model
Bert text classification
Data preparation and preprocessing
Text Generation Model

Project 2: Text Generation Model

Overview of Text Generation Model
Evaluation and fine-tuning
Evaluation and fine-tuning

Project 3: Designing a conversational agent architecture

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

Deployment and MLOps

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

Recommended Learning Methodology

Recommend allocating 1 hour daily to complete the course in 15 Days.

Though you can attempt the online exam anytime as per your convenience, we highly recommend attempting the exam within 10Days of course completion, as the subject will be fresh in your mind, and you get sufficient time to prepare/revise as well

Exam

Followed by the certification session, an exam will be conducted for a total of 100 marks.

You need to acquire 60+ marks to clear the exam.

If you fail to acquire 60+marks, you can retake the exam after one day.

The maximum number of retakes will be three.

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

Who Is a Certified LLM Developer™?

A Certified LLM Developer™ is a distinguished professional holding a certification that validates their exceptional expertise in large language models. These experts possess deep knowledge and skills in developing, fine-tuning, and deploying LLMs, enabling them to create sophisticated AI-driven solutions. They are innovators in AI, leveraging their expertise to build intelligent applications that can understand and generate human-like text across a wide range of domains. Certified LLM Developers play a pivotal role in advancing the capabilities of AI language models, contributing to the creation of groundbreaking applications and solutions in various industries.

Who Should Enroll for the Certified LLM Developer™ Certification?

This certification program is ideal for individuals passionate about artificial intelligence, natural language processing, and language models. It is designed for software developers, data scientists, AI researchers, and anyone interested in a career in AI-driven language modeling. Whether you’re an experienced professional seeking to deepen your expertise or new to the field, this certification provides the knowledge and skills necessary to excel in the rapidly evolving domain of large language models.

What Does a Certified LLM Developer™ Do?

Certified LLM Developer™ are proficient in developing, fine-tuning, and deploying large language models to create intelligent, context-aware applications. They utilize their expertise in LLM architectures, tools, and techniques to build AI models that can understand, generate, and interact with human language in a meaningful way. These experts work collaboratively with cross-disciplinary teams to incorporate LLM-driven solutions into various applications, from chatbots and virtual assistants to content generation and automated decision-making systems. Their role is crucial in ensuring the technical and functional excellence of AI-driven language models, driving innovation and efficiency in a wide range of industries.

What Are The Domains Where A Certified LLM Developer™ Works?

Tech and SaaS
Healthcare and AgriTech
E-commerce and Finance

Certification Benefits

Comprehensive Understanding of LLM Development: In-depth knowledge of LLM architectures, tools, and techniques for developing advanced AI-driven language models.
Validation of Expertise: Certification serves as tangible proof of your skills and expertise in LLM development, enhancing your credibility and marketability.
Career Advancement Opportunities: Opens doors to exciting career opportunities in AI development, natural language processing, data science, and more.
Industry Recognition: Gain recognition as a Certified LLM Developer, signaling to employers and peers that you possess the knowledge and skills to lead in the field of AI-driven language modeling.

Success Stories

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