Key Learning Outcomes
AI Integration in Business: Apply AI tools for data-driven insights, process automation, and decision-making.
Custom GPT Development: Develop and fine-tune GPT solutions to meet specific business needs.
Business Analytics: Leverage AI for descriptive and predictive analytics to support strategic decisions.
Workflow Automation: Use OpenAI tools to streamline operations and improve business efficiency.
Risk Analysis & Documentation: Perform AI-driven document analysis to uncover risks and generate actionable insights.
Lesson Plan
In this "Certified Gen AI Business Practitioner" program, you will learn how to use Generative AI tools to improve various business tasks. You'll discover how to create effective prompts, build AI agents, analyze data without coding, and automate processes with conversational AI, official documents, and risk analysis. The program includes practical examples and case studies to show how AI can be applied in real business situations.
View Course Schedule for Certified AI Business Practitioner
Module 1: Prompt Engineering for Business Users
You'll learn how to create effective prompts for business applications, including using personas and chain-of-thought techniques to improve AI responses.
1.1 Introduction to Prompt Engineering
Learn the fundamentals of prompt engineering and its role in AI-driven business solutions.
1.2 Basic Prompt Engineering and Best Practices
You will learn to design effective prompts for business applications, such as descriptive, instructional, and persona-based prompts, enabling you to generate insights, automate workflows, and drive innovation. By applying these techniques, you will optimize communication, enhance decision-making, and tailor solutions to specific business scenarios.
1.2.1 Descriptive Prompts: Create detailed and clear prompts to extract insights and improve analytics.
1.2.2 Instructional Prompts: Develop step-by-step prompts to guide AI in performing tasks accurately.
1.2.3 Creative Prompts: Design prompts for brainstorming innovative ideas or generating creative outputs.
1.2.4 Persona-Based Prompts: Tailor prompts to match specific business personas, improving customization.
1.2.5 Contextual Prompts: Incorporate context into prompts for more precise and relevant AI outputs.
1.2.6 Numbers & Data-Based Prompts: Leverage data-focused prompts to analyze metrics and drive insights.
1.3 Advanced prompting techniques
You will explore advanced techniques like variable prompting, mixing personas, and knowledge source integration to refine AI responses and automate complex workflows. These skills will empower you to leverage Gen AI for strategic business decisions and efficient process management.
1.3.1 Variable Prompting: Adapt prompts to different business scenarios using variables.
1.3.2 Mixing Variables & Personas: Combine multiple variables and personas for dynamic AI responses.
1.3.3 Knowledge Source Prompting: Integrate external knowledge into prompts to refine AI outputs.
1.3.4 Reasoner & Agents: Develop prompts that enable AI to reason and handle complex workflows.
Module 2: Custom GPT Development
Learn how to develop and fine-tune custom GPT models tailored to your business needs. This includes creating custom instructions, branding, developing intents, ensuring security, and managing ethical considerations to automate your enterprise business process.
2.1 Custom Instructions: Craft instructions to align GPT outputs with business goals.
2.2 Contextual Mapping: Link instructions with data sources for precise, context-aware responses.
2.3 Branding and Personalization: Customize GPTs to reflect your organization's tone, style, and needs.
2.4 Developing GPT Intents: Design intents to handle specific tasks or workflows effectively.
2.5 Fine-Tuning and Versioning: Train GPTs further to enhance accuracy and maintain updated versions.
2.6 Security and Ethical Biases: Ensure safe, ethical, and bias-free GPT deployments for enterprise use.
Module 3: AI Data Analytics - Descriptive & Predictive
Utilize AI as a synthetic data scientist to perform descriptive and predictive analytics without coding. Apply machine learning models to generate insights and support strategic decision-making.
3.1 AI for Analytics – Synthetic Data Scientist: Use AI to analyze synthetic data for real insights.
3.2 KPIs & Statistics with AI: Track business metrics effectively with AI tools.
3.3 Apply Machine Learning with No Code
3.3.1 Linear Regression: Forecast trends and identify correlations.
3.3.2 Decision Tree: Categorize data for easy decision-making.
3.3.3 Logistic Regression: Target outcomes based on historical data.
3.3.4 Random Forest: Enhance predictive accuracy with ensemble models.
3.3.5 Gradient Boosting: Optimize performance for complex business scenarios.
3.4 Generate Predictive Results: Use machine learning models for actionable predictions and strategic decisions.
View Course Schedule for Certified AI Business Practitioner
Module 4: Conversational AI for Business Automation
Design and implement conversational AI systems and multi-agent chatbots to automate business processes, enhance customer engagement, and improve operational efficiency.
4.1 Developing Custom Instructions for Chatbots: Tailor chatbot responses for business needs.
4.2 Design and Deploy Conversational AI Bots: Create functional chatbots for customer queries and operations.
4.3 Multi-Agent Chatbot Frameworks: Develop chatbots that interact across multiple nodes seamlessly.
4.4 Enterprise Business Process Automation: Automate enterprise workflows with AI-driven chatbots.
4.5 Case Study for Custom GPTs: Analyze real-world use cases and implement chatbot solutions.
Module 5: AI for Official Documentation and Risk Analysis
Use AI to analyze large volumes of documents, uncover risks and insights, prepare reports, and enhance communication with stakeholders.
5.1 Observe a Large Array of Documents: Analyze volumes of data to unlock actionable insights.
5.2 Unlock Risks, Insights, and Parameters: Use AI to uncover risks, conditions, and hidden patterns.
5.3 Prepare Documents: Automate document creation for reports and analysis.
5.4 Improve Stakeholder Communication: Enhance clarity and precision in stakeholder reporting.
5.5 Presentation: Summarize findings and communicate results effectively.
Module 6: AI Product Engineering & LLM Pricing Models
Understand the architecture of large language models (LLMs) and explore real-world use cases to improve business productivity. Learn about LLM pricing models to make informed decisions for your organization.
6.1 Understanding LLM Architecture: Learn about LLM components and their use cases in business.
6.2 Real-World Use Cases: Explore practical examples where LLMs enhance productivity and innovation.
Module 7: AI for Professional Communication & Personality Development
This module focuses on using AI tools to craft compelling resumes and optimize email communication for professional success. It covers advanced job search strategies, techniques to navigate AI-based job filters and methods for building a strong personal brand with AI.
7.1 Enhancing Resumes Using AI: Optimize resumes to match job requirements and highlight strengths.
7.2 Effective Email Communication Tools: Craft clear and impactful professional emails.
7.3 AI-Based Job Search Strategies: Use AI tools to navigate job markets and identify opportunities.
7.4 Techniques to Enhance Job Filters: Improve job search outcomes with AI-based filtering techniques.
7.5 Personal Branding with AI: Build and manage a strong professional brand using AI-driven tools.
View Course Schedule for Certified AI Business Practitioner
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