Generative AI Technical Masterclass
Instructor-led
Virtual / Classroom based
30 Hours
1-2-1 Coaching
Customized Content
Collaboration Ecosystem
For solution architects, developers, consultants, project managers, test engineers, system administrators etc., who want to gain technical knowledge on Generative AI
Why is this course needed?
PROBLEM
- Generative AI is a digital transformation technology that has the ability to enable business transformation.
- It is based on transformer architecture, an evolution of neural networks based architecture, the foundation of deep learning.
- There is plenty of technical material on generative AI available online comprising research papers, articles, blogs, videos, and social media posts.
- The technical material comprises complex texts and diagrams presented in a language and jargon followed by technical researchers and scientists.
- Technical professionals, business professionals, and students find it very difficult to comprehend
SOLUTION
- To drive AI/GenAI transformation, technical reskilling is extremely important
- Generative AI Technical Masterclass is designed to simplify complex AI/GenAI concepts, delivering high-quality, clear, and easy to apply practical knowledge
- It also covers GenAI 2.0 that focuses on scaling, operational readiness, multimodal and advance featured LLMs
Simpler version of complex transformer architecture taught in the Generative AI Technical Masterclass
WHAT MAKES THIS COURSE UNIQUE?
- Coaching to ensure practical application of competencies at workplace
- Call-to-Action to speed up your organization's AI/GenAI deployment
- Content Customization to differentiate from competitors
- Collaborative and continuous learning through ecosystems
Course Curriculum
Generative AI Primer
A quick recap of the prerequisite videos on generative AI
Evolution to Transformer based Architecture
Evolution from probabilistic or statistical to neural networks based to transformer based
Transformer based Architecture
Strong focus on self attention technique the heart of transformer based architecture
LLM Model Selection
Proven best practices of selecting an LLM model based on business requirements
Agent-driven Workflows
Key capabilities of agents and how they can add efficiencies in processes and workflows
Biases and Hallucinations
Understand the causes, detection, and mitigation of biases and hallucinations
GenAI 2.0
Scaling generative AI, operational readiness framework, advanced LLMs, technical ecosystem
Prompt Engineering
Learn the techniques of crafting effective prompts
Key Technical Concepts
Important concepts like learning algorithms, output evals, machine learning principles etc.
Fine Tuning LLMs
Introduction to different types of LLM Fine Tuning techniques
Generative AI Deployment
Know more about different data pipelines, LLMOps, and MLOps
Retrieval Augmentation Generation (RAG)
Need for RAGs, RAG architectures, different RAG techniques
Responsible AI for Techies
How technical professionals can ensure compliance with Responsible AI policies
Pilot Selection
Proven guidelines and best practices for selecting a scalable GenAI pilot