• Round-the-Clock Help
• After-Course Support
• Extensive Training Resources
• Ongoing Material Access
The Generative AI for Executives (GAIE) course aims to help executives, managers, and decision-makers from various industries comprehend the possibilities of generative artificial intelligence (AI) and how it might affect their operations and business strategy. Since no technical knowledge of AI is required, a variety of professionals can use it, including but not limited to:
• C-Level Executives
• Business Leaders
• Technology Leaders
• Innovation Officers
• Decision-Makers in Data-Driven Roles
• Industry Professionals
• Product Managers
• Marketing and Sales Managers
• Innovation and R&D Leaders
• Strategy and Planning Executive
Although there is no specific course to give as a requirement, learners enrolling in this course should have some prior knowledge of the following.
• Basic Understanding of AI and Machine Learning
• Data Literacy
• Business Acumen
• Curiosity and Openness to Learning
• Familiarity with the fundamentals of data and Azure cloud
• No prior knowledge of Generative AI is required
The course is led by mentors in a dynamic and engaging learning environment, allowing the participants to become experts in the following fields:
• Examine the concepts of generative AI.
• Use text preparation and text categorization algorithms.
• Describe the meanings of variational autoencoders (VAEs) and autoencoders.
• Put GANs to use in generative AI tasks.
• Recognize the various kinds of language models and the uses for them.
• Use transformer-based models for a range of applications.
• Explain what prompt engineering is and why it matters.
• Make carefully thought-out prompts for generative AI activities.
• Make sense of the Large Language Models (LLMs) project lifecycle in Generative AI.
• Describe how LLMs are used in text production, prediction, and search activities.
• Carry out LLM pre-training and optimization.
• Put LLMs into practice and adjust parameters according to particular guidelines.
• Put into practice LLM-based activities like next-word prediction and search query completion.
• Make a LangChain application to generate valuable applications.
• Recognize the elements of Retrieval-Augmented Generation (RAG).
• Evaluate LLM performance with human assessment and metrics such as BLEU score and perplexity.
• Examine various generative AI tools and their real-world applications
Virtual Instructor-Led Session
- 2 days Instructor led Online Training
- Experienced Subject Matter Experts
- Approved and Quality Ensured training Material
- 24*7 leaner assistance and support
Customized According To Team's Requirements
- Customized Training Across Various Domains
- Instructor Led Skill Development Program
- Ensure Maximum ROI for Corporates
- 24*7 Learner Assistance and Support
• AI Overview
• Traditional Systems vs Machine Learning-based AI
• Taxonomy of AI
• Capabilities & Use Cases
• AI & Data Science
• Types of Machine Learning
• Understanding ML Algorithms in an Intuitive Way
• Introduction to Deep Learning
• Ways to Implement AI
• Demos on Sentiment Analysis of Tweets and Pictures
• Introduction to Generative AI
• Evolution of Generative AI
• How Generative AI Differs from Other AI Technologies
• Understanding Generative AI and its Capabilities
• Distinctions Between Generative AI and Traditional AI/ML
• Exploring the Generative AI Value Chain
• Current Trends in Generative AI, including ChatGPT
• Applications and Use Cases of Generative AI
• Demos to give a broader perspective about Bard, ChatGPT, MidJourney, and more
• Organizational Requirements for Generative AI Adoption
• Preparing the Organization for Generative AI Integration
• Skillsets and Expertise Required for Implementing Generative AI
• Overcoming Challenges and Managing Risks in Generative AI Adoption
• Strategic Initiatives for Incorporating AI
• Building an AI-First Company Culture
• Vision, Risks, Assumptions, Acceptance and more
• Integrating Generative AI into Business Processes
• Exploring Opportunities for AI Innovation and Growth
• Adopting Generative AI Strategy
• Importance of Well-Defined Prompts in Generative AI
• Strategies for Crafting Effective Prompts
• Leveraging Prompt Engineering for Desired Outputs
• Lab Exercise on better prompt design
• Cloud Computing and its Impact on Generative AI
• Data Collection, Privacy, and Security Considerations
• Leveraging Data for Improving Generative AI Performance
• Ethical and Responsible AI
• Understanding Ethical Concerns in Generative AI
• Responsible Use of Generative AI Technologies
• Building Trustworthy AI Systems
• Future Trends and Opportunities in Generative AI
• Exploring the Potential of Generative AI in Different Industries
• Anticipating Advancements and Innovations in Generative AI
• Identifying Opportunities for Business Growth and Competitive Advantage
• Demo on Cloud AI
• Implementing a Generative AI Strategy
• Key considerations for integrating Generative AI into existing workflows
• Identifying use cases and projects suitable for Generative AI adoption
• Evaluating ROI and cost-benefit analysis of Generative AI implementation
• Addressing biases and fairness in Generative AI models
• Understanding the potential societal impact of Generative AI
• Developing ethical guidelines for using Generative AI responsibly
AI Strategy Consultant
AI Product Manager
Vinsys works with you to identify the areas where you need to develop and receive training. We provide a variety of training alternatives, such as private group training, on-site instruction at your convenience, and virtual training. Our training courses and certification programs align with the goals of your business.
Vinsys faculty have an average of twenty years of practical experience in information technology. Trainers spend at least twenty-five percent of their time studying new and developing courses and technology to stay current.
The curriculum will be presented with live software exercises, practical assignments, and interactive lectures. Working on individual and group projects will be necessary for learners to gain expertise in Generative AI for Executives (GAIE).
The trainers get 30 to 180 days to use the lab after the course. A lab training key will be provided to each participant so they can connect to a remote lab environment during and after the course.
Vinsys is an excellent location for training because of its outstanding support system and authorized training programs. Apart from resources to aid them in maximizing value for the client, superior assistance is consistently available. Vinsys consultants are adept at recognizing the value of technology and incorporating it into the overall business strategy. Vinsys maintains a comprehensive view while paying meticulous attention to details to guarantee that the system meets and exceeds requirements.
The course is for 02-days.
According to a recent survey by the global professional services network KPMG, over three-quarters of CEOs consider generative AI a "top investing priority." It is worthwhile investing in AI to boost the companies' profitability, innovation, and security.