Overview

This is a comprehensive two-day course designed for non-technical mid-level and senior managers aiming to deepen their understanding of Artificial Intelligence. This course covers fundamental AI concepts, explores the intricacies of Generative AI, and demonstrates practical ways AI can boost productivity within organizations. Through interactive sessions, case studies, and discussions on the latest AI technologies, participants will gain valuable insights into leveraging AI for strategic advantage.

Skills Covered

  • Have a solid understanding of AI fundamentals and key technologies.
  • Understand the workings and applications of Generative AI, including ChatGPT, Gemini, and Midjourney.
  • Be able to identify opportunities where AI can enhance productivity and efficiency.
  • Recognize the ethical and societal implications of AI technology.
  • Know how to initiate and manage AI projects within their organizations.
  • Be prepared to lead their teams in adopting AI solutions.

Prerequisites

  • Basic familiarity with digital technologies and business operations.
  • An open-minded approach to learning and innovation.
  • No prior technical experience in AI is required.
  • Subscription for Midjourney is recommended but not required
  • Google account

Target Audience

Everyone who is interested.

Course Curriculum

Module 1: Understanding AI and Its Capabilities
1.1. Foundations of AI

1.1.1. Introduction to Artificial Intelligence

1.1.2. Evolution of AI: From Concept to Reality

1.1.3. Understanding Machine Learning, Deep Learning, and Neural

 

Networks

1.2. Generative AI Technologies

1.2.1. Exploring Generative AI: ChatGPT, Gemini, Midjourney

1.2.2. Capabilities and Limitations of Generative AI

1.2.3. Practical Applications: Content Creation, Design, Decision Support

1.3. AI in Business: Enhancing Productivity

1.3.1. AI Solutions for Business Process Optimization

1.3.2. Case Studies: AI in Marketing, HR, Customer Service, and More

1.3.3. Measuring the Impact of AI on Productivity

1.4. Ethical Considerations in AI

1.4.1. Bias, Privacy, and Security Concerns

1.4.2. Ethical AI Design and Use

1.4.3. Regulatory Landscape for AI Technologies
Module 2: Implementing AI Solutions
2.1. Data Science and AI

2.1.1. Role of Data in AI: Collection, Preparation, and Analysis

2.1.2. Introduction to Data Science Techniques for AI

2.1.3. Understanding the Importance of Data Quality and Integrity

2.2. Developing and Deploying AI Projects

2.2.1. Identifying Opportunities for AI in Your Organization

2.2.2. Steps for Developing an AI Project: From Idea to Implementation

2.2.3. Overcoming Challenges in AI Adoption: Talent, Infrastructure, and Cost

2.3. Future of AI and Strategic Planning

2.3.1. Emerging Trends in AI and Their Potential Impact

2.3.2. Preparing for the Future: Building an AI-Ready Organization

2.3.3. Developing a Strategic AI Roadmap for Your Business

2.4. Workshop and Group Discussion

2.4.1. Hands-on Workshop: Exploring AI Tools and Platforms

2.4.2. Group Discussion: Sharing Insights and Experiences

2.4.3. Developing Personalized Action Plans for AI Adoption
Module 3: Conclusion and Q&A
3.1. Recap of Key Insights and Learnings

3.2. Open Forum for Final Questions

3.3. Guidance on Next Steps and Resources for Continued Learning

Dates & Locations

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Exam & Certification

This course is not associated with any Certification.

Training & Certification Guide

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