AI & MACHINE LEARNING FOR BUSINESS PRACTICES

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COURSE OVERVIEW

This course provides participants with a comprehensive understanding of the fundamental concepts and principles of Artificial Intelligence (AI). It covers the basics of AI, its applications, and its potential impact on various industries. Participants will gain insights into the key components of AI, including machine learning, neural networks, natural language processing, and robotics. Through a combination of theoretical lectures and practical exercises, participants will develop a solid foundation in AI and its real-world applications.

COURSE OBJECTIVES

By completely attending this course, participants will be able to:

  • Define and explain the core concepts of Artificial Intelligence.
  • Identify various AI technologies and their applications in different industries.
  • Understand the principles of machine learning and its algorithms.
  • Describe the basics of neural networks and their role in AI.
  • Explain the fundamentals of natural language processing and its use cases.
  • Comprehend the ethical and societal implications of AI technologies.
  • Apply basic AI techniques to solve simple problems.
business man holding artificial intelligence icon with half brain and half circuit 3d rendering

TARGET COMPETENCIES

  • AI fundamentals
  • Basic AI techniques application
  • Understand Machine learning and application
  • Deep learning and NLP foundation
  • Robotics basic functions, applications, automation and synergy

Professionals seeking an introduction to Artificial Intelligence and understanding how AI is transforming industries. Business leaders looking to explore AI applications for their organizations. Anyone professionals curious about the principles and possibilities of AI.

The course will be delivered through a combination of interactive lectures. The consultant will present an engaging presentation to introduce theoretical concepts. The consultant will lead hands-on exercises to apply AI techniques using simple programming languages. Other activities introduced in the course are case Studies from real-world examples showcasing AI applications in diverse sectors, group and Q&A Sessions.

INTRODUCTION TO ARTIFICIAL INTELLIGENCE

  • Defining AI and its historical context
  • Types of AI: Narrow vs. General AI
  • Impact of AI on society and industries.

MACHINE LEARNING FUNDAMENTALS

  • Basics of machine learning: Supervised, unsupervised, reinforcement learning
  • Training and testing data
  • Regression and classification algorithms.

NEURAL NETWORKS AND DEEP LEARNING

  • Understanding neural networks and their architecture
  • Deep learning applications: Image recognition, language translation
  • Introduction to popular frameworks (e.g., TensorFlow, PyTorch).

NATURAL LANGUAGE PROCESSING (NLP)

  • NLP overview and challenges
  • Text preprocessing and tokenization
  • Sentiment analysis and language generation

AI ETHICS AND CONSIDERATIONS

  • Ethical implications of AI: Bias, privacy, job displacement
  • AI regulations and guidelines

AI IN PRACTICE

  • Case studies across industries: Healthcare, finance, manufacturing, etc.
  • Implementing a simple AI project: From idea to execution

FUTURE TRENDS AND BEYOND

  • Emerging trends in AI: Explainable AI, AI for social good, etc.
  • AI’s role in shaping the future.

INTRODUCTION TO ROBOTIC APPLICATIONS AND AI INTEGRATION

BASICS OF ROBOTIC APPLICATIONS

  • Overview of robotics in diverse industries
  • Key roles of robotics in streamlining operations.

ROBOTICS AND AI SYNERGY

  • Understanding the connection between robotics and artificial intelligence
  • Role of AI in enhancing robotic capabilities.

ROBOTIC PROCESS AUTOMATION

  • Introduction to RPA and its relevance in business processes
  • Use cases: Data entry, customer support, workflow automation.

CASE STUDIES: AI-DRIVEN ROBOTIC SOLUTIONS

  • Real-world examples showcasing AI-integrated robotics.
  • Analysis of benefits and efficiencies achieved through AI-robotics synergy.
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