Duration
3 Days
Level
Basic Level
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As per your team needs
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The course is designed to empower participants with the knowledge and hands-on skills needed to excel in the dynamic field of generative AI. This transformative learning journey delves into the core concepts, ethical considerations, and practical applications of generative AI, equipping participants to harness its potential for becoming more effective and knowledgeable about this domain.
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- Software developers and engineers who are interested in incorporating AI into their applications
- Anyone who is interested to learn and implement Generative AI
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- Introduction to Generative AI
- Generative AI Use Cases
- Key Generative AI Platforms and Tools
- An Introduction to OpenAI Platform
- Generative AI on GCP
- Ethical Considerations
- Demonstration(s)
- BARD
- Gemini
- ChatGPT
- OpenAI Developer Platform
- Getting started with AI
- Types of AI
- Discriminative AI vs Generative AI
- Natural Language Processing (NLP) Overview
- Evolution of NLP
- Understanding Embeddings
- Tokenizing Text
- Demonstration(s)
- Tokenization – https://platform.openai.com/tokenizer
- Visualization of Embedding
- Introduction to Large Language Models (LLMs)
- Limitations
- Key LLMs and their capabilities
- Pricing aspects
- Demonstration(s)
- Working with Chat LLM on GCP
- Working with Completion LLM on GCP
- Ways to build GenAI Applications
- Challenges with Prompt Engineering
- Pre-trained Models vs Fine Tuned Models
- Finetuning vs RAG Based Approach
- Demonstration(s)
- Finetuning Model on GCP using your own data
- The Power of Prompts
- Prompt Design Principles
- Zero Shot vs Few Shot learning
- Demonstration(s)
- Making use of ChatGPT/BARD as a Pro user
- Understanding how to interact with Gemini Model
- Building Text Generation Application
- Productionalize Application
- Demonstration(s)
- Working with Gemini APIs using Jupyter Notebooks
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- Curiosity to learn
- Programming background
- Knowledge of Python will be a plus
