About SNA Technologies:
SNA Technologies Inc. (SNAT), established in 2006 and headquartered in Michigan, USA, is a global leader in IT solutions and training. We specialize in AI-driven training and consulting services to elevate the technical expertise of IT professionals worldwide. As a member of The Open Group, we contribute to global standards in enterprise architecture and IT solutions. Our highly experienced team is dedicated to providing advanced AI education, tailored to senior professionals seeking to enhance their knowledge in AI applications and leadership.
Why Choose SNA?
The Generative AI for Senior Professionals course is designed to provide a deep dive into advanced concepts of Generative AI. This course is perfect for senior professionals who want to enhance their knowledge of AI applications and strategically leverage these technologies for their organizations. Through in-depth exploration of Large Language Models (LLMs), optimization, fine-tuning, and practical use cases, this course equips senior professionals with the insights needed to make AI-powered decisions in the workplace.
Key reasons to choose SNA for your Generative AI training:
– In-depth, executive-level insights into the capabilities of Generative AI.
– Real-world applications and use cases to drive AI initiatives.
– Focus on advanced LLM concepts, fine-tuning, and optimization for strategic value.
– 16 hours of intensive training, with a focus on leadership and implementation.
Course Approach
The Generative AI for Senior Professionals course is designed to provide a comprehensive understanding of Generative AI, including the latest advancements in large language models, optimization techniques, and practical applications. This course combines theory with real-world use cases and strategic insights, allowing professionals to lead AI-driven initiatives within their organizations effectively.
Summary
The Generative AI for Senior Professionals course provides a robust understanding of advanced Generative AI concepts. It is designed for professionals who wish to harness the power of AI in their leadership roles, focusing on LLM optimization, fine-tuning, and practical applications such as Retrieval-Augmented Generation (RAG) and Large Action Models.
Learning Goals
By the end of the course, participants will be able to:
– Gain a comprehensive understanding of advanced concepts in Generative AI.
– Explore real-world use cases and how to apply Generative AI within their organizations.
– Understand and optimize large language models (LLMs) for business-specific needs.
– Leverage RAG (Retrieval-Augmented Generation) and Vector Databases in AI systems.
– Fine-tune LLMs for specific applications and business use cases.
– Learn about Large Action Models and their role in enhancing decision-making processes.
Topics Covered (16 Hours)
- Basic Concepts of Generative AI
– Overview of Generative AI and its potential to transform industries.
– Key generative models and their role in AI-driven solutions.
– Impact of Generative AI on business operations, content creation, and customer engagement.
- Use Cases of Generative AI
– Real-world applications of Generative AI in different industries.
– Use cases in customer service, marketing, and content generation.
– How Generative AI is enhancing productivity and efficiency in business.
- Basic Concepts of Large Language Models (LLM)
– Introduction to LLMs and their importance in natural language processing (NLP).
– Business applications of LLMs in text generation, summarization, and conversational AI.
– Overview of popular LLMs (e.g., GPT, BERT) and their capabilities.
- Optimization of LLM
– Techniques for optimizing LLMs for specific tasks and business needs.
– Improving efficiency and cost-effectiveness of LLM applications.
– Considerations for optimizing LLMs in real-world use cases.
- Retrieval-Augmented Generation (RAG)
– Introduction to RAG and its impact on Generative AI systems.
– How RAG improves accuracy by integrating external data sources.
– Business applications of RAG in personalized content generation.
- Vector Databases
– Understanding the role of Vector Databases in AI and machine learning.
– Efficiently storing and retrieving high-dimensional data for AI applications.
– Practical applications of Vector Databases in Generative AI systems.
- Fine-Tuning of LLM
– How to fine-tune LLMs for specific use cases and business applications.
– Best practices for fine-tuning LLMs to improve model performance.
– Fine-tuning for enhanced customer interaction, automation, and data processing.
- Introduction to Large Action Models
– Exploring Large Action Models (LAM) and their role in decision-making.
– How LAMs enhance automated actions based on AI-driven insights.
– Applications of LAM in business operations, including real-time decision-making.
What Attendees Get
Course registration includes:
– Comprehensive course materials and workbooks.
– In-depth case studies and practical exercises.
– Networking opportunities with industry professionals and experts.
– Certificate of Completion upon successful course completion.
Who Will Benefit?
This course is ideal for:
– Senior executives, managers, and decision-makers looking to harness AI for business strategy.
– IT leaders responsible for implementing AI-driven solutions across their organizations.
– Senior professionals looking to stay ahead of AI trends and integrate Generative AI into business operations.
– Business leaders in industries such as finance, marketing, and customer service seeking to innovate with AI technologies.
Prerequisites
No formal prerequisites are required, but familiarity with business technology strategies, as well as a basic understanding of AI concepts, will be beneficial.
Professional Development Units (PDUs)
Participants may be eligible to apply for PDUs towards continuing education requirements with relevant certification bodies.
Course Features
- Lectures 0
- Quizzes 0
- Duration 2 days
- Skill level All levels
- Language English
- Students 0
- Assessments Yes
