Introduction to AI & Machine Learning
Artificial Intelligence (AI)
COURSE OVERVIEW
This intensive two-day foundational training program is designed to provide participants with a clear and practical understanding of Artificial Intelligence (AI) and Machine Learning (ML). The course introduces core concepts, key technologies, and real-world applications while also exploring emerging trends shaping the future of AI.
Participants will gain a solid conceptual foundation in AI, including machine learning principles, deep learning, NLP, and computer vision, enabling them to understand how modern intelligent systems are built and applied across industries..
COURSE OBJECTIVES
By the end of this course, participants will be able to:
- Understand the fundamentals and evolution of Artificial Intelligence.
- Explain key Machine Learning concepts and learning types.
- Identify real-world applications of AI across industries.
- Gain a basic understanding of deep learning, NLP, and computer vision.
- Recognize ethical considerations and responsible AI practices.
- Explore current and future trends in AI technologies.
- Build a strong foundation for advanced AI/ML learning paths.
Duration: 2 Days / 16 Hours
Delivery Method: Classroom-based, Virtual Instructor Led Training
COURSE OUTLINE
Day 1: Fundamentals of AI and Machine Learning
Focus: Building core understanding of AI and ML concepts
- Introduction to Artificial Intelligence (AI)
- History and evolution of AI technologies
- Overview of Machine Learning (ML)
- Difference between AI, ML, and Deep Learning
- Types of Machine Learning:
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Basic understanding of algorithms and models
- AI applications across industries (healthcare, finance, retail, manufacturing, etc.)
- Real-world AI use cases and examples
- Hands-on discussion: Identifying AI in everyday systems
Day 2: AI Technologies and Future Trends
Focus: Exploring modern AI technologies and direction of the field
- Introduction to Deep Learning concepts
- Overview of Neural Networks (high-level understanding)
- Basics of Natural Language Processing (NLP)
- Introduction to Computer Vision concepts
- AI in automation and intelligent systems
- Ethics in AI:
- Bias in AI systems
- Data privacy concerns
- Responsible AI usage
- Future trends in AI:
- Generative AI
- Autonomous systems
- AI in business transformation
- Emerging technologies and career opportunities in AI
Wrap-up discussion: Future impact of AI in industries
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