Generative AI Prompt Engineering - Professional Course

Upgrade your practical Generative AI skills with Cronus Consultants’ Generative AI Professional Course. Learn Python for AI, Large Language Models, prompt engineering, RAG, vector databases, multimodal AI, AI application development, AI agents, deployment, security, and responsible AI through structured learning and hands-on projects.

6 Months
Online / offline

Why Choose Cronus Consultants for Generative AI?

Cronus Consultants’ Generative AI program takes learners from AI foundations and Python to advanced LLM applications, RAG systems, multimodal content creation, and AI deployment. The curriculum combines conceptual learning with practical tools and project-based training to help learners understand how Generative AI is developed, integrated, and applied in real-world scenarios.

Curriculum Overview

Download Syllabus

Understand the transition from traditional Machine Learning to Deep Learning and Generative AI, with Python, NumPy, and Pandas for AI data workflows.
Explore neural networks, transformer architecture, and how Large Language Models differ from traditional predictive models.

Explore leading LLMs such as GPT-4, Llama 3, and Google Gemini, along with their capabilities and applications.
Learn advanced prompt engineering, few-shot prompting, Chain of Thought, ethical prompting, and the fundamentals of model fine-tuning.

Understand RAG architecture and learn how LLMs can connect with private data sources to improve contextual responses and reduce hallucinations.
Work with vector databases such as Pinecone or Weaviate to store, search, and retrieve high-dimensional data embeddings.

Explore text-to-image and video workflows using tools such as DALL-E, Midjourney, and Stable Diffusion.
Use AI coding tools and agents such as GitHub Copilot for code generation, translation, review, and documentation across creative and business applications.

Build end-to-end AI applications using frameworks and ecosystems such as LangChain and Hugging Face.
Learn deployment approaches using platforms such as NVIDIA NIM and Google Vertex AI, with an introduction to AI microservices.

Understand responsible AI practices for mitigating bias, protecting data privacy, managing hallucinations, and improving AI safety.
Explore Agentic AI and autonomous systems capable of performing multi-step tasks with limited human intervention.

Build a hands-on Generative AI project integrating LLMs, prompt engineering, RAG, AI tools, application development, and relevant AI workflows.
Gain practical experience in deployment, cloud storage, testing, project execution, and final project presentation.

Key Features

LLM & Prompt Engineering

Master LLM concepts and prompt engineering techniques.

RAG & Vector Databases

Build AI applications connected to private data sources.

Multimodal AI

Create AI-powered text, image, video, audio, and code content.

AI Application Development

Build, deploy, and secure practical Generative AI applications.

Who can pursue this course?

BBA B.A. B.Sc(Computer Science) M.Sc (Computer Science) B.TECH M.TECH Commerce MBA

      
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