Generative AI Engineer

Python Course

The Python Course Basic to Advance provides learners with a strong foundation in Python programming for Generative AI development. Participants learn Python syntax, variables, data types, operators, control statements, loops, functions, object-oriented programming, file handling, exception handling, and modular programming. Through hands-on coding exercises and real-world AI projects, learners develop the programming skills required to build intelligent applications, automate workflows, integrate AI models, and create scalable software solutions for modern Generative AI environments.

OpenAI API Course

The OpenAI API Course Basic to Advance equips learners with the skills to integrate OpenAI's large language models into enterprise AI applications. Participants explore API authentication, chat completions, structured outputs, function calling, embeddings, streaming responses, prompt optimization, error handling, rate limiting, and secure API integration. Through practical implementation projects, the course prepares learners to develop intelligent AI assistants, business automation solutions, and production-ready Generative AI applications.

LangChain Course

The LangChain Course Basic to Advance focuses on building intelligent AI workflows using the LangChain framework. Learners master prompt templates, chains, agents, memory, document loaders, output parsers, tools, Retrieval-Augmented Generation (RAG), workflow orchestration, and external system integration. The course emphasizes practical implementation through enterprise AI projects that combine large language models with business data and knowledge sources.

LlamaIndex Course

The LlamaIndex Course Basic to Advance provides comprehensive training in developing knowledge retrieval systems for Generative AI applications. Participants learn document ingestion, indexing strategies, query engines, retrieval optimization, metadata management, hybrid search, evaluation techniques, and integration with vector databases and language models. The course develops practical expertise in building scalable Retrieval-Augmented Generation (RAG) solutions for enterprise environments.

Hugging Face Course

The Hugging Face Course Basic to Advance equips learners with the skills to utilize open-source transformer models for Generative AI applications. Participants explore pretrained models, tokenizers, pipelines, text generation, embeddings, fine-tuning concepts, inference optimization, model deployment, model hub usage, and integration with Python applications. Through hands-on AI projects, the course prepares learners to build intelligent applications using state-of-the-art transformer technologies.

Pinecone Course

The Pinecone Course Basic to Advance focuses on implementing scalable vector databases for semantic search and Retrieval-Augmented Generation applications. Learners master vector indexing, embeddings storage, similarity search, namespaces, metadata filtering, performance optimization, security, scalability, and LangChain integration. The course enables participants to build high-performance knowledge retrieval systems for enterprise AI solutions.

ChromaDB Course

The ChromaDB Course Basic to Advance teaches learners how to build lightweight vector database solutions for Generative AI applications. Participants learn document collections, embedding management, similarity search, indexing, metadata handling, persistence, retrieval optimization, local deployment, and integration with LangChain and LlamaIndex. Through practical implementation projects, the course develops expertise in creating efficient semantic search systems.

Ollama Course

The Ollama Course Basic to Advance provides learners with practical skills for running and managing open-source large language models locally. Participants explore model installation, local inference, model management, prompt execution, API integration, performance optimization, custom model configuration, privacy-focused AI deployment, and integration with LangChain and LlamaIndex. The course prepares learners to build secure, offline, and cost-effective Generative AI applications using local LLMs.

Streamlit Course

The Streamlit Course Basic to Advance equips learners with the skills to build interactive web applications for Generative AI solutions. Participants learn interface design, widgets, session state, file uploads, chat interfaces, API integration, data visualization, deployment, performance optimization, and user experience design. Through hands-on projects, the course enables learners to develop professional AI-powered applications, chatbots, and enterprise dashboards with intuitive and responsive user interfaces.