AISEMTMaster ClassMT-AISE1.0<p>Why Choose This Training Program?</p> <ul> <li>Practical Skills: Go beyond the theory with real-world exercises, role-playing sessions, and workshop-style learning.</li><li>Industry-Relevant Content: Gain insights into how AI is transforming sectors such as healthcare, finance, retail, and more.</li><li>Expert Guidance: Led by seasoned professionals with years of experience in AI sales and technology.</li></ul><p>This training is ideal for sales professionals, account managers, and business development teams who want to sharpen their AI knowledge and improve their ability to sell AI-related products and services.</p><h5>Day 1:</h5><ul> <li>Foundations of AI and Generative AI: Gain a clear understanding of AI and GenAI, explore current trends, and learn to identify market opportunities.</li><li>AI Technologies and Tools: Discover the core technologies behind AI, the necessary hardware and software requirements, and how to integrate AI solutions into customer environments.</li></ul><h5>Day 2:</h5><ul> <li>AI Product and Service Sales: Develop strategies to present AI offerings convincingly, address customer concerns, and highlight the tangible benefits of AI solutions.</li><li>Proven Sales Techniques and Best Practices: Learn how to craft compelling pitches, build long-term customer relationships, and implement a winning AI sales strategy.</li></ul><h4>Day 1: Basics and Use Cases</h4><h5>Module 1: Introduction to AI and GenAI</h5><h6>Contents:</h6><ul> <li>Definitions and Concepts: <ul> <li>AI: Overview of various AI types, from rule-based systems to deep learning.</li><li>GenAI: Explanation of generative models that produce content such as text, images, or music.</li><li>AI Agents: Interactive systems that independently perform tasks based on user interactions and environmental data.</li></ul></li><li>Historical Development: <ul> <li>Key milestones in AI development.</li><li>From symbolic AI to machine learning and the era of GenAI.</li></ul></li><li>Market Potential and Current Trends: <ul> <li>Global market size and growth rates in the AI sector.</li><li>Relevant industries: healthcare, retail, financial services, manufacturing.</li><li>Emerging technologies: transformer models, multimodal AI systems, AutoML.</li></ul></li></ul><h6>Activity/Exercise:</h6><ul> <li>Group Work: <ul> <li>Participants analyze the most common use cases in their respective industries.</li><li>Creation of a short presentation: How can AI/ GenAI/ AI agents deliver concrete improvements?</li></ul></li></ul><h5>Module 2: Technologies and Tools for AI Solutions (3 hours)</h5><h6>Contents:</h6><ul> <li>AI Technology Basics: <ul> <li>Difference between supervised, unsupervised, and reinforcement learning methods.</li><li>Structure of neural networks and how they recognize patterns in data.</li><li>Functionality of generative models such as GANs (Generative Adversarial Networks) and transformer architectures (e.g., GPT).</li></ul></li><li>Hardware and Software Resources: <ul> <li>GPUs, TPUs, and other specialized hardware for AI training and inference.</li><li>Cloud services (e.g., AWS, Azure, Google Cloud) for AI projects.</li><li>Open-source libraries: TensorFlow, PyTorch, Hugging Face Transformers.</li></ul></li><li>Integrations and APIs: <ul> <li>Overview of RESTful APIs and SDKs.</li><li>Ways to integrate AI models into existing software landscapes.</li><li>Security and privacy considerations when using AI services.</li></ul></li></ul><h6>Activity/Exercise:</h6><ul> <li>Practical Demonstration: <ul> <li>Participants work in groups with a simple generative model application, such as text or image generators.</li><li>They compare results and discuss implementation opportunities and challenges.</li></ul></li></ul><h4>Day 2: Sales and Customer Focus</h4><h5>Module 3: Selling AI Products and Services</h5><h6>Contents:</h6><ul> <li>Understanding Products and Services: <ul> <li>Differences between AI services (e.g., APIs, consulting), software products (e.g., pre-built AI solutions), and hardware solutions (e.g., AI-optimized hardware).</li><li>Use cases and benefits for various target audiences.</li></ul></li><li>Communicating Customer Value: <ul> <li>Presenting success stories and case studies.</li><li>Addressing common customer concerns (e.g., data sovereignty, implementation costs) and how to handle them.</li></ul></li><li>Industry Examples: <ul> <li>Using GenAI in marketing campaigns.</li><li>AI agents for process automation in call centers.</li><li>Hardware solutions for AI-powered image analysis in healthcare.</li></ul></li></ul><h6>Activity/Exercise:</h6><ul> <li>Role-playing: <ul> <li>Participants practice sales conversations with different customer types.</li><li>Peers act as customers, raising typical questions and objections.</li><li>Feedback session: Strengths and improvement areas.</li></ul></li></ul><h5>Module 4: Strategies and Best Practices for AI Sales</h5><h6>Contents:</h6><ul> <li>Developing Sales Strategies: <ul> <li>Market segmentation: How to identify potential customers.</li><li>Targeted outreach: Personalizing offers based on customer profiles.</li><li>Up-selling and cross-selling: Building a portfolio that extends beyond a single solution.</li></ul></li><li>Building Customer Relationships: <ul> <li>Ongoing engagement with customers: Collecting feedback and deriving improvements.</li><li>Long-term customer retention through training and support.</li></ul></li><li>Best Practices: <ul> <li>Case studies of successful AI implementations.</li><li>Key dos and don&rsquo;ts in the sales process.</li><li>Adapting to technological changes and continuous learning strategies for sales teams.</li></ul></li></ul><h6>Activity/Exercise:</h6><ul> <li>Workshop: <ul> <li>Participants create a short pitch deck for an AI product or service.</li><li>Presentation in front of the group, followed by a feedback session.</li><li>Goal: Develop a convincing sales presentation that is practical and engaging.</li></ul></li></ul><h5>Summary and Wrap-Up</h5><ul> <li>Open discussion about lessons learned.</li><li>Addressing any remaining questions.</li><li>Participants receive a brief summary of the discussed topics and links to additional resources.</li></ul>Why Choose This Training Program? - Practical Skills: Go beyond the theory with real-world exercises, role-playing sessions, and workshop-style learning. - Industry-Relevant Content: Gain insights into how AI is transforming sectors such as healthcare, finance, retail, and more. - Expert Guidance: Led by seasoned professionals with years of experience in AI sales and technology.This training is ideal for sales professionals, account managers, and business development teams who want to sharpen their AI knowledge and improve their ability to sell AI-related products and services.Day 1: - Foundations of AI and Generative AI: Gain a clear understanding of AI and GenAI, explore current trends, and learn to identify market opportunities. - AI Technologies and Tools: Discover the core technologies behind AI, the necessary hardware and software requirements, and how to integrate AI solutions into customer environments. Day 2: - AI Product and Service Sales: Develop strategies to present AI offerings convincingly, address customer concerns, and highlight the tangible benefits of AI solutions. - Proven Sales Techniques and Best Practices: Learn how to craft compelling pitches, build long-term customer relationships, and implement a winning AI sales strategy.Day 1: Basics and Use Cases Module 1: Introduction to AI and GenAI Contents: - Definitions and Concepts: - AI: Overview of various AI types, from rule-based systems to deep learning. - GenAI: Explanation of generative models that produce content such as text, images, or music. - AI Agents: Interactive systems that independently perform tasks based on user interactions and environmental data. - Historical Development: - Key milestones in AI development. - From symbolic AI to machine learning and the era of GenAI. - Market Potential and Current Trends: - Global market size and growth rates in the AI sector. - Relevant industries: healthcare, retail, financial services, manufacturing. - Emerging technologies: transformer models, multimodal AI systems, AutoML. Activity/Exercise: - Group Work: - Participants analyze the most common use cases in their respective industries. - Creation of a short presentation: How can AI/ GenAI/ AI agents deliver concrete improvements? Module 2: Technologies and Tools for AI Solutions (3 hours) Contents: - AI Technology Basics: - Difference between supervised, unsupervised, and reinforcement learning methods. - Structure of neural networks and how they recognize patterns in data. - Functionality of generative models such as GANs (Generative Adversarial Networks) and transformer architectures (e.g., GPT). - Hardware and Software Resources: - GPUs, TPUs, and other specialized hardware for AI training and inference. - Cloud services (e.g., AWS, Azure, Google Cloud) for AI projects. - Open-source libraries: TensorFlow, PyTorch, Hugging Face Transformers. - Integrations and APIs: - Overview of RESTful APIs and SDKs. - Ways to integrate AI models into existing software landscapes. - Security and privacy considerations when using AI services. Activity/Exercise: - Practical Demonstration: - Participants work in groups with a simple generative model application, such as text or image generators. - They compare results and discuss implementation opportunities and challenges. Day 2: Sales and Customer Focus Module 3: Selling AI Products and Services Contents: - Understanding Products and Services: - Differences between AI services (e.g., APIs, consulting), software products (e.g., pre-built AI solutions), and hardware solutions (e.g., AI-optimized hardware). - Use cases and benefits for various target audiences. - Communicating Customer Value: - Presenting success stories and case studies. - Addressing common customer concerns (e.g., data sovereignty, implementation costs) and how to handle them. - Industry Examples: - Using GenAI in marketing campaigns. - AI agents for process automation in call centers. - Hardware solutions for AI-powered image analysis in healthcare. Activity/Exercise: - Role-playing: - Participants practice sales conversations with different customer types. - Peers act as customers, raising typical questions and objections. - Feedback session: Strengths and improvement areas. Module 4: Strategies and Best Practices for AI Sales Contents: - Developing Sales Strategies: - Market segmentation: How to identify potential customers. - Targeted outreach: Personalizing offers based on customer profiles. - Up-selling and cross-selling: Building a portfolio that extends beyond a single solution. - Building Customer Relationships: - Ongoing engagement with customers: Collecting feedback and deriving improvements. - Long-term customer retention through training and support. - Best Practices: - Case studies of successful AI implementations. - Key dos and don’ts in the sales process. - Adapting to technological changes and continuous learning strategies for sales teams. Activity/Exercise: - Workshop: - Participants create a short pitch deck for an AI product or service. - Presentation in front of the group, followed by a feedback session. - Goal: Develop a convincing sales presentation that is practical and engaging. Summary and Wrap-Up - Open discussion about lessons learned. - Addressing any remaining questions. - Participants receive a brief summary of the discussed topics and links to additional resources.2 days1950.001950.001950.001950.001690.001950.00