Artificial Intelligence (A.I.) for Managers (with Industry Use Cases)
Artificial Intelligence (A.I.) is revolutionizing the business landscape, offering unprecedented opportunities for innovation and efficiency. This two-day online course is designed to equip managers with the knowledge and skills to leverage A.I. in their organizations. Through a combination of theoretical insights, industry use cases, and hands-on activities, participants will gain a comprehensive understanding of A.I. and its strategic applications.
Key Learnings:
- Understand fundamental A.I. concepts and terminologies
- Explore different types of A.I. technologies and their real-world applications
- Analyze industry-specific use cases of A.I.
- Develop strategies for implementing A.I. solutions in business
- Address ethical considerations and challenges in A.I. deployment
- Gain practical experience in building a simple A.I. model
- Familiarize with popular A.I. tools and platforms
- Learn how to foster an A.I.-ready culture within organizations
- Identify career paths and opportunities in the field of A.I. for managers
Course Content:
Day 1: Understanding AI and Its Applications
- Welcome and course objectives
- Overview of the agenda
Introduction to Artificial Intelligence
- What is AI?
- History and evolution of AI
- Key concepts and terminologies
Types of AI Technologies
- Machine Learning (Supervised, Unsupervised, Reinforcement Learning)
- Natural Language Processing (NLP)
- Computer Vision
- Robotics
- Expert Systems
AI in Industry – Use Cases
- Healthcare: Predictive diagnostics, personalized medicine
- Finance: Fraud detection, algorithmic trading
- Retail: Customer recommendations, inventory management
- Manufacturing: Predictive maintenance, quality control
- Marketing: Customer segmentation, sentiment analysis
AI Implementation Strategies
- Identifying business problems for AI solutions
- Data collection and preparation
- Selecting the right AI tools and technologies
- Building and training AI models
Ethical Considerations and Challenges in AI
- Bias and fairness in AI
- Data privacy and security
- Transparency and explainability
- Regulatory and legal issues
Day 2: Practical AI Implementation and Career Path Guidance
AI Project Lifecycle
- Project scoping
- Data collection and preprocessing
- Model development and training
- Model deployment and monitoring
Hands-on Workshop: Developing a Simple AI Model
- Selecting a use case (e.g., customer churn prediction)
- Data exploration and preprocessing
- Building and training a machine learning model
- Evaluating model performance
AI Tools and Platforms
- Overview of popular AI tools (TensorFlow, PyTorch, Scikit-learn)
- AI as a Service (AIaaS) platforms (Google AI, AWS AI, Microsoft Azure AI)
- Case studies of successful AI implementations using these tools
Building an AI-Ready Culture
- Encouraging innovation and experimentation
- Training and upskilling teams
- Collaborating with AI experts and consultants
- Creating an AI governance framework
Career Path in AI for Managers
- Roles and responsibilities in AI projects
- Skills and qualifications needed
- Career progression and opportunities
- Building a personal learning path
Prerequisites:
- No prior knowledge of A.I. is required
- Basic understanding of business and management principles
- Familiarity with data-driven decision-making processes is beneficial
Career Path
- AI Project Manager
- AI Consultant
- Business Intelligence Manager
- Data Science Manager
- Strategic Planning Manager
- Innovation Manager
International Student Fees: USD175$
Job Interview Preparation (Soft Skills Questions & Answers)
- Tough Open-Ended Job Interview Questions
- What to Wear for Best Job Interview Attire
- Job Interview Question- What are You Passionate About?
- How to Prepare for a Job Promotion Interview
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Flexible Class Options
- Week End Classes For Professionals SAT | SUN
- Corporate Group Training Available
- Online Classes – Live Virtual Class (L.V.C), Online Training
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