Certified AI Solution Architect

Upcoming Certified AI Solution Architect Program:

Dates and Sessions: Each session is 4 hours, featuring interactive learning, hands-on breakout exercises designed to provide real-world experience in building AI-driven solutions.

• 16th November 2024: Session 1
• 17th November 2024: Session 2 
• 23rd November 2024: Session 3
• 24th November 2024: Session 4
• 30th November 2024: Session 5
• 1st December 2024: Session 6
• 7th December 2024: Session 7
• 8th December 2024: Session 8
• 14th December 2024: Session 9

In this immersive program, participants will learn to design, architect, and deploy AI solutions using no-code development platforms, machine learning tools, natural language processing (NLP) services, automation platforms, and app-building interfaces. Each session features a hands-on breakout exercise, allowing you to apply what you’ve learned immediately and build a functional AI agent step by step.

Duration: 36 hours Instructor-Led Live Online Training

Training Schedule: Session Timing: 2:30 PM to 6:30 PM (Sundays)

Exclusive Offer: Unlock limited-time discounts with early registration!

Certification: Globally recognised accredited by Exemplar Global

Certificate Validity: Lifetime

Roles and Responsibilities of AI Solution Architect

Designing AI Architectures:

• Craft scalable, secure, and efficient AI system architectures.

• Select appropriate technologies and frameworks that align with project requirements.

Aligning Technology with Business Goals:

• Work closely with stakeholders to identify business challenges and opportunities.

• Develop AI strategies that contribute to achieving organizational objectives.

Overseeing Implementation:

• Provide guidance during the development process to ensure adherence to the architectural vision.

• Collaborate with development teams to address technical challenges and optimize performance.

Ensuring Compliance and Ethical Standards:

• Implement data governance policies to protect sensitive information.

• Advocate for ethical AI practices within the organization.

Continuous Learning and Innovation:

• Stay abreast of the latest advancements in AI and related technologies.

• Promote a culture of innovation by exploring new tools and methodologies.

Offered as

a. Online Instructor-led
b. Public Training – Calendar Program
c. Corporate Program – Standard or Customized, Continuous or Knowledge Area wise

Who Can Benefit

• Senior Management Professionals looking to lead AI initiatives.

• Technical Leads and Developers aiming to step into strategic roles.

• Business Analysts and Consultants who want to enhance their AI proficiency.

• Aspiring AI Architects seeking to formalize their skills and knowledge.

Integrating External Data SourcesCertified AI Solution Architect (CAISA)

Course Outline

Session 1: Foundations of AI 

Objectives:

• Understand the fundamental concepts and types of AI.
• Recognize the impact of AI in today’s business environment across various industries.
• Comprehend the basics of Conversational AI and its components.
• Compare major Conversational AI platforms: Claude, ChatGPT, Copilot, and Gemini.
• Identify Intent Search platforms like Perplexity and AI development platforms such as Botpress, RASA, Amazon Lex, CustomGPT, and Voiceflow.
• Recognize how these platforms can be leveraged to enhance business processes and customer interactions.
• Gain hands-on experience in designing conversational flows, implementing NLU for understanding user queries, and integrating the KB for providing dynamic responses.

Breakout Activity:

• Activity: Participants will design a basic conversational flow, create intents, and integrate a knowledge base to provide dynamic responses.

Content:

I. Introduction to Artificial Intelligence (AI)

II. AI in Today’s Business Environment

III. Basics of Conversational AI

IV. Enhancing Customer Interactions with Conversational AI

V. Comparing Major Conversational AI Platforms

VI. Introduction to Intent Search Platforms

VII. Overview of AI Development Platforms

VIII. Preparing for AI Solutions with These Platforms

Session 2: Theoretical Foundations of Machine Learning and Advanced Conversational AI Features

Objectives:

• Define Machine Learning and distinguish it from traditional programming.
• Understand different types of Machine Learning and their applications.
• Comprehend key concepts in supervised learning, especially classification tasks.
• Explain advanced features in no-code conversational AI platforms, including context management, slot filling, multi-turn dialogs, and conditional logic.
• Recognize how these features help handle complex queries and ambiguous inputs.
• Understand how conversational AI agents manage context to deliver personalized experiences.
• Prepare to design complex, branching conversational flows using conditional logic.

Breakout Activity:

• Activity: Participants will design and build a conversational AI agent using advanced features such as context management, slot filling, multi-turn dialogs, and conditional logic to handle complex, multi-turn conversations.

Content:

I. Introduction to Machine Learning

II. Types of Machine Learning

III. Key Concepts in Supervised Learning

IV. Advanced Features in No-Code Conversational AI Platforms

V. Handling Complex Queries and Ambiguous Inputs

VI. Context Management and Dialog Design

VII. Practical Applications and Examples

Session 3: Introduction to Natural Language Processing and Large Language Models (LLMs)

Objectives:

• Grasp the fundamental concepts of NLP and its significance in AI.
• Understand what Large Language Models (LLMs) are and how they enhance NLP capabilities.
• Recognize key NLP techniques such as tokenization, intent recognition, and entity extraction.
• Identify practical applications of NLP and LLMs in various domains.
• Learn how to utilize NLP and LLM features within Voiceflow without coding.
• Acknowledge ethical considerations in NLP related to privacy, bias, and transparency.
• Prepare for hands-on experience with Voiceflow and LLMs in the upcoming session.

Breakout Activity:

• Activity: Participants will create a conversational agent in Voiceflow that leverages Large Language Models (LLMs) to handle complex user inputs and generate dynamic, context-aware responses.

Content:

I. Introduction to Natural Language Processing (NLP)

II. Understanding Large Language Models (LLMs)

III. NLP and LLMs in Conversational AI with Voiceflow

IV. Ethical Considerations in NLP and LLMs

V. Preparing for Hands-On Experience with Voiceflow and LLMs

Session 4: AI Business Requirements, Ethics, Governance, and Security

Objectives:

• Comprehend the importance of Business Requirement Documents (BRDs) in AI projects.
• Identify the key components and best practices for creating effective BRDs.
• Understand ethical principles and real-world considerations in AI development.
• Recognize the components and significance of AI governance.
• Learn about unique security challenges in AI and best practices to mitigate them.
• Incorporate ethics, governance, and security considerations into BRDs.
• Analyze case studies to understand the practical applications of these concepts.

Breakout Activity:

• Activity: Participants will create a BRD (Business Requirements Document) and analyze ethical considerations for AI projects.

Content:

I. Introduction to AI Business Requirements

II. Best Practices for BRD Creation

III. Ethics in AI

IV. AI Governance

V. Security Challenges in AI

VI. Components of AI Governance

VII. Case Studies and Examples

Session 5: Advanced Knowledge Base Integration and Optimization in Conversational AI

Objectives:

• Understand advanced Knowledge Base (KB) concepts and their significance in conversational AI.
• Structure and optimize Knowledge Bases for efficient retrieval and scalability.
• Integrate external data sources using APIs to enhance AI agent capabilities.
• Apply best practices for optimizing performance and user experience in AI agents.
• Prepare for hands-on activities involving advanced KB integration and optimization.

Breakout Activity:

• Activity: Participants will integrate an advanced Knowledge Base into a conversational AI agent using Voiceflow, optimize it for efficient information retrieval, and enhance its capabilities by connecting to external data sources via APIs.

Content:

I. Advanced Knowledge Base (KB) Concepts

II. Structuring and Optimizing Knowledge Bases

III. Integrating External Data Sources

IV. Best Practices for Optimization

V. Hands-On Integration with Voiceflow

Session 6: Process Automation with Zapier and AppSheet Integration

Objectives:

• Understand the fundamentals of process automation and its benefits.
• Familiarize yourself with Zapier and how it automates workflows between applications.
• Learn how to build simple applications using AppSheet without coding.
• Identify practical applications of process automation in various domains.
• Prepare for practical integration of these tools with AI agents using Voiceflow.

Breakout Activity:

• Activity: Participants will automate workflows by integrating their AI agents with Zapier and AppSheet, creating seamless processes that trigger actions based on user interactions with the chatbot.

Content:

I. Introduction to Process Automation

II. Automating Workflows with Zapier

III. Introduction to AppSheet

IV. Integrating Process Automation with AI Agents

V. Preparing for Hands-On Integration

Session 7: Generative AI Integration

Objectives:

• Implement advanced integration techniques of Generative AI within Voiceflow.
• Master advanced prompt engineering to effectively guide AI responses.
• Understand strategies for managing response unpredictability and ensuring content appropriateness.
• Optimize performance and scalability when using Generative AI in conversational agents.
• Address ethical and compliance considerations in deploying Generative AI at scale.
• Prepare for practical implementation and discussion in the upcoming live session.

Breakout Activity:

• Activity: Participants will integrate advanced Generative AI features into a conversational agent using Voiceflow. The focus will be on advanced prompt engineering, performance optimization, managing ethical considerations, and enhancing user interactions through sophisticated AI responses.

Content:

I. Recap of Generative AI and LLMs

II. Advanced Integration of Generative AI with Voiceflow

III. Accessing and Configuring Generative AI APIs and Integrating them into AI agent.

IV. Advanced Ethical and Compliance Considerations

V. Advanced Conversational Design with Generative AI

Session 8: Fine-Tuning and Advanced Prompt Engineering for Generative AI

Objectives:

• Understand the concept and importance of fine-tuning in Generative AI.
• Learn various methods of fine-tuning, including training with custom datasets, prompt engineering, and parameter adjustments.
• Recognize the limitations and considerations associated with fine-tuning AI models.
• Master advanced prompt engineering techniques to craft effective prompts and control AI behavior.
• Familiarize yourself with tools and platforms for developing and testing prompts, including prompt debuggers, prompt generation platforms, and prompt repositories.
• Develop strategies for balancing predefined content with AI-generated responses in conversational agents.
• Understand how to integrate user feedback to continuously improve AI agent performance.
• Grasp the ethical and compliance considerations involved in fine-tuning AI model

Breakout Activity:

• Activity: Participants will fine-tune their AI agents, adjusting prompts and configurations for more accurate and relevant responses.

Content:

I. Understanding Fine-Tuning Concepts

II. Advanced Prompt Engineering

III. Tools for Prompt Engineering

IV. Balancing Predefined and AI-Generated Content

V. Continuous Improvement Through User Feedback

Session 9: Dynamic Content Generation and Optimization

Objectives:

• Understand advanced techniques for dynamic content generation in AI agents.
• Identify performance bottlenecks and apply optimization strategies.
• Grasp the principles of designing scalable AI solutions.
• Learn how to integrate all components of your AI agent for a cohesive user experience.
• Acquire presentation skills and techniques to effectively communicate your AI solution.
• Recognize the importance of ethical and compliance considerations in AI development.
• Prepare for the final presentation and certification requirements.

Breakout Activity:

• Activity: Participants will finalize and present their optimized AI agent, demonstrating its dynamic content generation and scalability.

Content:

I. Advanced Techniques in Dynamic Content Generation

II. Performance Optimization

III. Designing Scalable AI Solutions

IV. Integrating All AI Components for a Cohesive User Experience

V. Presentation Skills for AI Solutions

VI. Final Preparation for Certification

Corporate Workshops Tailored to Your Needs
Benchmark Six Sigma offers customized versions of this program as corporate workshops, designed to meet your organization’s unique requirements. Elevate your team’s capabilities with hands-on, real-world training tailored to your business goals.