In the dynamic landscape of modern enterprises, the strategic adoption of Artificial Intelligence (AI) isn't just an advantage—it's a necessity. For senior management and team leaders, understanding, embracing, and leveraging AI is the key to steering your organization towards unprecedented success. Welcome to a transformative two-day journey— "AI For Management & Decision Makers." This immersive course is more than theory; it's a tailored experience where insights meet practical application, equipping you to lead your organization into an AI-powered future.

Training Duration: 2 Days

SBL-Khas Claimable
Certificate Of Completion Available
Private In-House Class Available
ILT & VILT Class Available

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CLZK-AIMDM: AI For Management & Decision Makers

RM2,699.00

RM1,889.00

In a world where innovation drives success, harnessing the power of Artificial Intelligence (AI) is no longer an option but a strategic imperative. The two-day immersive course on "Implementing AI in Your Organization" is your ticket to understanding, embracing, and leveraging the transformative potential of AI in your corporate landscape.

From revolutionizing industries to redefining business strategies, AI has emerged as the cornerstone of modern enterprise. This course isn't just about theory; it's a dynamic journey crafted exclusively for senior management, where theory meets application, and insights meet actionable strategies.

Day One embarks on an exhilarating exploration of AI fundamentals. You'll dive deep into the AI ecosystem, unraveling its various branches—Machine Learning, Deep Learning, NLP, and Computer Vision—unlocking their potential and demystifying their applications through real-world success stories. Discover how data isn't just information; it's the lifeblood of AI, and learn how to wield its power ethically and effectively within your organization.

Day Two is the bridge between theory and implementation, where strategies take shape, and vision meets action. You'll craft a tailored AI strategy, mapping the pathway for seamless integration into your business operations. Dive into the intricacies of project management, navigate ethical considerations, and confront legal complexities with confidence. Through practical sessions and immersive workshops, you'll unravel the mysteries of AI implementation, equip yourself with best practices, and empower your team to drive change effectively.

This course isn't just about AI; it's about empowering you to lead the charge in your organization's AI journey. It's about fostering a culture of innovation, navigating complexities with finesse, and steering your company towards a future where AI isn't just a tool but a strategic advantage.
Upon completing the course, participants should be able to:

Define the core concepts of AI and differentiate between various types and applications of AI in different industries.

Identify and explain the key AI technologies and techniques, including Machine Learning, Deep Learning, NLP, and Computer Vision.

Understand the pivotal role of data in AI implementation, including data collection, quality, and governance.

Evaluate the ethical implications of AI deployment and apply ethical considerations to AI projects.

Formulate an AI strategy aligned with organizational objectives, considering readiness, resources, and potential ROI.

Navigate the AI project lifecycle, from inception to deployment, managing teams, risks, and challenges effectively.

Analyze and address ethical and legal concerns surrounding AI implementation within their organization.

Implement practical steps for deploying AI solutions, monitoring performance, and fostering a culture conducive to AI adoption.

Identify emerging trends in AI and devise strategies for continuous learning and adaptation in the rapidly evolving AI landscape.
Senior Management

Team Leader
Define and differentiate types of AI and its applications across industries.

Comprehend key AI technologies and techniques (Machine Learning, Deep Learning, NLP, Computer Vision).

Demonstrate an understanding of the significance of data in AI and its governance.

Apply ethical considerations to AI projects and their implications.

Development of an AI strategy aligned with organizational goals and addressing readiness, resources, and potential ROI.

Navigate the AI project lifecycle, including team management and risk mitigation strategies.

Recognise emerging trends in AI and their potential impact on the organization.

Development of strategies for continuous learning and adaptation in the evolving AI landscape.
Module 1:   Introduction to AI

Overview of AI and its impact on businesses

Different types of AI: narrow vs. general AI

Emerging trends and innovations in AI

Real-world applications and success stories in various industries

Module 2:   AI Technologies in Depth

Machine Learning: Supervised, Unsupervised, and Reinforcement Learning

Deep Learning and Neural Networks

Natural Language Processing (NLP) and Computer Vision

Large Language Model

Overview of readily existing AI frameworks and tools in the market

Module 3:   Data as the Foundation of AI

Importance of data in AI implementation

Data quality, collection, and preprocessing

Interpreting the Confusion Matrix

Data governance and ethical considerations in AI

Module 4:   AI in Business Strategy

Integrating AI into business strategy and operations

Identifying AI opportunities and challenges in the corporate landscape

Assessing organizational readiness for AI adoption

Formulating an AI strategy aligned with corporate goals

Case studies of successful AI integration in companies

Module 5:   Weighing Matrices for RFPs in AI Vendor Selection

Identifying and defining crucial selection criteria for AI vendor evaluation

Designing a comprehensive weighing matrix for evaluating vendor proposals.

Applying the weighing matrix to objectively evaluate and compare vendor proposals.

Module 6:   Budgeting and Financing for AI Projects

ROI metrics for AI: defining and measuring success beyond financial gains.

Quantitative and qualitative evaluation criteria for assessing AI project success.

Calculating and interpreting ROI for AI projects: cost reduction, revenue generation, and intangible benefits.

Module 7:   AI Project Management

Understanding the AI project lifecycle

Team composition and skills required for AI projects

Risk management and overcoming common pitfalls in AI implementation

Best practices for monitoring, evaluating, and iterating AI systems

Change management and fostering a culture conducive to AI adoption

Module 8:   Ethical and Legal Aspects of AI

Ethical considerations in AI development and deployment

Ensuring fairness, transparency, and accountability in AI systems

Legal compliance and regulatory frameworks related to AI

CLZK-AIMDM: AI For Management & Decision Makers

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