Applied Artificial Intelligence 

This course offers a hands-on journey into applied artificial intelligence, designed for professionals seeking to integrate AI into business, marketing, development, and automation. Participants learn how to harness AI tools not only for productivity but also for innovation, strategy, and customer engagement. The program combines foundational knowledge with practical applications, enabling learners to drive measurable outcomes in their organizations.

Module 1: Foundations of Applied AI

Objective: Establish a strong understanding of AI principles, prompt engineering, and modern AI tools for professional use.

1.1: Applied AI Overview

• The current AI ecosystem: LLMs, Generative AI, and industry applications

• Ethical considerations, governance, and responsible AI use

1.2: Mastering Prompt Engineering

• Crafting effective prompts: role, context, task, and output format

• Iterative refinement and advanced prompting strategies

1.3: The AI Workbench

• Exploring integrated AI platforms (ChatGPT, Claude, Copilot, etc.)

• Specialized tools for writing, coding, and analysis

1.4: AI for Continuous Learning

• Using AI as a tutor, researcher, and learning accelerator

Module 2: AI for Productivity and Workflow Automation

Objective: Learn how AI enhances everyday tasks, office tools, and process automation.

2.1: Intelligent Document Development

• Drafting reports, proposals, and policies with AI

• Summarization, grammar refinement, and tone adjustment

2.2: AI-Enhanced Spreadsheets

• AI formulas in Spreadsheets

• Automating data cleaning, formatting, and calculations

• VBA (Visual Basic for Applications) scripts

2.3: Smart Presentations

• Generating outlines, slides, and with AI tools

2.4: Task Automation with Scripts

• Writing batch files, macros, and system automation scripts

Module 3: AI for Data, Analytics and Business Intelligence

Objective: Use AI to analyze data, generate insights, and support strategic decisions.

3.1: AI for Database Management

• Generating SQL queries from natural language

• Designing and optimizing databases with AI

3.2: AI in Data Visualization

• Conversational data analysis

• Creating dashboards, charts, and infographics

3.3: AI-Powered Business Intelligence

• Predictive analytics, forecasting, and decision support

• Integration with BI tools (Power BI, Tableau, etc.)

3.4: Market Research with AI

• Competitor analysis, consumer sentiment, and trend identification

Module 4: AI in Content Creation and Digital Marketing

Objective: Apply AI to enhance marketing, branding, and content strategy.

4.1: AI for Blogging and Social Media

• Content ideation, calendars, and post creation

• Automating publishing workflows

4.2: AI-Driven SEO

• Keyword research, meta descriptions, and optimization strategies

4.3: Email Marketing and Automation

• Drafting persuasive emails and automated campaign flows

4.4: AI in Digital Marketing Campaigns

• Audience targeting and personalization

• Campaign analysis and performance optimization

4.5: AI for Marketing Materials

• Generating brochures, ads, and visuals

Module 5: AI for Development and Innovation

Objective: Accelerate software, website, and app development with AI-assisted tools.

5.1: AI in Software Development

• Programming with AI

• Testing, debugging, and documentation

5.2: AI for Website Development

• Rapid prototyping in HTML, CSS, and JavaScript

• AI tools for responsive design and optimization

5.3: AI in App Development

• Wireframing and UI/UX prototyping with AI

• Generating backend and API code snippets

5.4: AI-Generated Scripts and Media

• Writing scripts for videos, podcasts, and training modules

Module 6: AI for Customer Engagement and Experience

Objective: Design and implement AI-driven solutions for improved customer interactions.

6.1: Conversational AI and Chatbots

• Building AI-powered chat support systems

• Training bots with custom datasets and knowledge bases

6.2: AI in Customer Journey Mapping

• Personalization strategies using AI insights

• Predicting customer needs and behavior

Module 7: AI Security and Ethical Considerations

Objective: Understand the security risks associated with AI and learn to identify AI-generated content and misinformation.

7.1: The Landscape of AI Security Risks

• Adversarial attacks: Prompt injection, data poisoning

• Model theft and privacy breaches

7.2: Identifying Synthetic Media (Deepfakes)

• Detecting AI-generated images, video, and audio

• Tools and techniques for verification

7.3: Combating AI-Driven Misinformation

• Understanding the spread of fake news

• Ethical guidelines and responsible AI deployment

Project: AI-Driven Transformation Strategy

Objective: Learners apply concepts from all modules to design a comprehensive AI integration plan for a business case of their choice (e.g., marketing automation, customer support chatbot, BI dashboard, or AI-assisted development project).