Course Information
Duration
24 hrs
Level
Academic
Language
English
Exam Information
Exam Code
SG-343
Total Questions
60
Duration
60 mins
Passing %
60%
Pre-requisite
Prerequisites for an "AI and ML for Business Bootcamp" include basic programming skills (preferably Python), a grasp of statistical concepts, proficiency in data analysis, and fundamental business understanding. This bootcamp is designed to equip participants with practical AI and ML skills tailored for business applications
Course Description
AI and ML for Business Bootcamp - Join our intensive AI and ML for Business Bootcamp to bridge the gap between data science and business success. From foundational concepts to hands-on applications, this program is tailored for professionals seeking to harness the power of AI and ML in business contexts. Gain expertise in data analysis, machine learning algorithms, and strategic implementation for impactful decision-making. Acquire practical skills through real-world projects, ensuring you emerge ready to drive innovation and efficiency in your business endeavors
Course Objectives
1. Gain a solid foundation in the fundamental concepts of Artificial Intelligence (AI) and Machine Learning (ML), including key terminology, algorithms, and basic principles.
2.Explore practical applications of AI and ML in various industries. Understand how these technologies can be leveraged to drive business value, improve efficiency, and create new opportunities. Managers should be able to identify potential use cases for their specific business context and evaluate their feasibility.
3.Examine the ethical implications and regulatory frameworks surrounding AI and ML.
4.Equip managers with the knowledge and skills to integrate AI and ML into strategic decision-making processes.
5.Foster effective communication between managers and technical teams working on AI and ML projects.
Course Curriculum
- Understanding the Impact of AI and ML
- The Evolution of Artificial Intelligence
- Real-World Applications and Success Stories
- Exploring Machine Learning Concepts
- Types of Machine Learning Algorithms
Key Terminology and Concepts
- The Role of AI and ML in Modern Business
- Leveraging AI for Competitive Advantage
Building an AI-Driven Business Strategy
- Harnessing the Power of Data
- AI for Predictive Analytics
- Optimizing Business Processes
- Data Collection and Preparation
- Model Training and Evaluation
- Deployment and Maintenance
- Real-World Examples of AI and ML Integration
- Successes and Challenges and Lessons Learned
- Personalization and Customer Segmentation
- Sales Forecasting and Lead Scoring
- Market Automation
- Algorithmic Trading and Investment Strategies
- Credit Scoring and Risk Management
- Fraud Detection
- Inventory Optimization
- Demand Forecasting
- Supply Chain efficiency
- Recruiting and Talent Acquisition
- Employee Engagement and Retention
- Workforce Planning
- Bias and Fairness in AI
- Privacy and Data Protection
- Responsible AI Practices
- Legal Frameworks and Regulations
- Compliance and Governance
- The Role of Business Managers in Ensuring Compliance
