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12x Your Business with AI: Proven Techniques for Revenue and Productivity Boost Course

12x Your Business with AI: Proven Techniques for Revenue and Productivity Boost Course

Unlock the Potential of AI to Grow Your Business: Proven Strategies for Increasing Revenue and Productivity

  • Category AI & ML
12x Your Business with AI: Proven Techniques for Revenue and Productivity Boost Course

What you'll learn

  • Fundamentals of AI and Machine Learning
  • Natural Language Processing (NLP)
  • Prompt Engineering
  • Hands-On Experience with AI Tools:
  • AI Ethics and Responsible AI
  • Advanced AI Topics

Course Syllabus

Introduction to AI
  • General AI
  • Superintelligent AI)";i:4;s:40:"Applications of AI in Various Industries";}
  • a:5:{i:0;s:35:"Overview of Artificial Intelligence";i:1;s:27:"History and Evolution of AI";i:2;s:28:"Key Concepts and Terminology";i:3;s:56:"Types of AI (Narrow AI
Fundamentals of Machine Learning
  • Clustering
  • Decision Trees
  • etc.)";i:3;s:31:"Model Evaluation and Validation";i:4;s:29:"Introduction to Deep Learning";}
  • a:5:{i:0;s:32:"Introduction to Machine Learning";i:1;s:32:"Introduction to Machine Learning";i:2;s:68:"Key Algorithms (Linear Regression
Natural Language Processing (NLP)
  • GPT
  • Lemmatization
  • Named Entity Recognition)";i:3;s:49:"Introduction to Language Models (BERT
  • etc.)";i:4;s:19:"Applications of NLP";}
  • a:5:{i:0;s:13:"Basics of NLP";i:1;s:29:"Text Preprocessing Techniques";i:2;s:72:"Common NLP Tasks (Tokenization
Applications of NLP
  • a:4:{i:0;s:27:"What is Prompt Engineering?";i:1;s:27:"Importance and Applications";i:2;s:43:"Key Principles of Writing Effective Prompts";i:3;s:31:"Understanding AI Model Behavior";}
Prompt Engineering Techniques•
  • Translation
  • etc.)";i:4;s:37:"Best Practices for Prompt Engineering";}
  • a:5:{i:0;s:26:"Basic Prompting Techniques";i:1;s:29:"Advanced Prompting Techniques";i:2;s:28:"Iterative Prompt Development";i:3;s:71:"Using Prompts for Different AI Tasks (Summarization
Hands-On with AI Tools
  • DALL-E
  • GPT-4
  • etc.)";i:1;s:32:"Practical Exercises and Examples";i:2;s:24:"Building Custom Chatbots";i:3;s:24:"Automating Tasks with AI";}
  • a:4:{i:0;s:52:"Working with AI Tools (ChatGPT
AI Ethics and Responsible AI
  • a:4:{i:0;s:28:"Ethical Considerations in AI";i:1;s:30:"Bias and Fairness in AI Models";i:2;s:29:"Privacy and Security Concerns";i:3;s:41:"Guidelines for Responsible AI Development";}
AI Integration and Deployment
  • a:4:{i:0;s:32:"Integrating AI into Applications";i:1;s:21:"Deployment Strategies";i:2;s:37:"Monitoring and Maintaining AI Systems";i:3;s:41:"Case Studies of Successful AI Deployments";}
Advanced Topics in AI
  • a:4:{i:0;s:22:"Reinforcement Learning";i:1;s:38:"Generative Adversarial Networks (GANs)";i:2;s:21:"AI in Computer Vision";i:3;s:27:"AI for Predictive Analytics";}
Case Studies and Projects
  • a:3:{i:0;s:20:"Real-World Use Cases";i:1;s:29:"Guided Projects and Exercises";i:2;s:32:"Q&A and Troubleshooting Sessions";}

Course Syllabus

  • Overview of Artificial Intelligence
  • History and Evolution of AI
  • Key Concepts and Terminology
  • Types of AI (Narrow AI, General AI, Superintelligent AI)
  • Applications of AI in Various Industries

  • Introduction to Machine Learning
  • Introduction to Machine Learning
  • Key Algorithms (Linear Regression, Decision Trees, Clustering, etc.)
  • Model Evaluation and Validation
  • Introduction to Deep Learning

  • Basics of NLP
  • Text Preprocessing Techniques
  • Common NLP Tasks (Tokenization, Lemmatization, Named Entity Recognition)
  • Introduction to Language Models (BERT, GPT, etc.)
  • Applications of NLP

  • What is Prompt Engineering?
  • Importance and Applications
  • Key Principles of Writing Effective Prompts
  • Understanding AI Model Behavior

  • Basic Prompting Techniques
  • Advanced Prompting Techniques
  • Iterative Prompt Development
  • Using Prompts for Different AI Tasks (Summarization, Translation, etc.)
  • Best Practices for Prompt Engineering

  • Working with AI Tools (ChatGPT, GPT-4, DALL-E, etc.)
  • Practical Exercises and Examples
  • Building Custom Chatbots
  • Automating Tasks with AI

  • Ethical Considerations in AI
  • Bias and Fairness in AI Models
  • Privacy and Security Concerns
  • Guidelines for Responsible AI Development

  • Integrating AI into Applications
  • Deployment Strategies
  • Monitoring and Maintaining AI Systems
  • Case Studies of Successful AI Deployments

  • Reinforcement Learning
  • Generative Adversarial Networks (GANs)
  • AI in Computer Vision
  • AI for Predictive Analytics

  • Real-World Use Cases
  • Guided Projects and Exercises
  • Q&A and Troubleshooting Sessions

Requirements

  • Good wifi
  • Laptop

Description

12x Your Business with AI: Proven Techniques for Revenue and Productivity Boost Course

This comprehensive course provides an in-depth exploration of artificial intelligence and prompt engineering.

  • This comprehensive course offers a detailed exploration of artificial intelligence and prompt engineering, providing a thorough understanding of key concepts and practical applications.
  • Gain insight into the history of AI, various types, and machine learning fundamentals, including supervised and unsupervised learning, key algorithms, and model evaluation.
  • Learn essential text preprocessing techniques and common NLP tasks in natural language processing (NLP), as well as the importance of effective prompt engineering and understanding AI model behavior.
  • Explore advanced prompting techniques and best practices, with hands-on sessions using AI tools like ChatGPT, GPT-4, and DALL-E to build custom chatbots and automate tasks.
  • Dive into AI ethics, focusing on bias, fairness, privacy, and security considerations, while also exploring advanced AI topics such as reinforcement learning, GANs, and predictive analytics with real-world case studies and guided projects.

Who this course is for:

  • Aspiring AI and Machine Learning Professionals
  • Data Scientists and Analysts
  • Researchers and Academics
  • Business Leaders and Managers

Meet your instructors

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Shiva Krishnan

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Course Syllabus

Introduction to AI
  • General AI
  • Superintelligent AI)";i:4;s:40:"Applications of AI in Various Industries";}
  • a:5:{i:0;s:35:"Overview of Artificial Intelligence";i:1;s:27:"History and Evolution of AI";i:2;s:28:"Key Concepts and Terminology";i:3;s:56:"Types of AI (Narrow AI
Fundamentals of Machine Learning
  • Clustering
  • Decision Trees
  • etc.)";i:3;s:31:"Model Evaluation and Validation";i:4;s:29:"Introduction to Deep Learning";}
  • a:5:{i:0;s:32:"Introduction to Machine Learning";i:1;s:32:"Introduction to Machine Learning";i:2;s:68:"Key Algorithms (Linear Regression
Natural Language Processing (NLP)
  • GPT
  • Lemmatization
  • Named Entity Recognition)";i:3;s:49:"Introduction to Language Models (BERT
  • etc.)";i:4;s:19:"Applications of NLP";}
  • a:5:{i:0;s:13:"Basics of NLP";i:1;s:29:"Text Preprocessing Techniques";i:2;s:72:"Common NLP Tasks (Tokenization
Applications of NLP
  • a:4:{i:0;s:27:"What is Prompt Engineering?";i:1;s:27:"Importance and Applications";i:2;s:43:"Key Principles of Writing Effective Prompts";i:3;s:31:"Understanding AI Model Behavior";}
Prompt Engineering Techniques•
  • Translation
  • etc.)";i:4;s:37:"Best Practices for Prompt Engineering";}
  • a:5:{i:0;s:26:"Basic Prompting Techniques";i:1;s:29:"Advanced Prompting Techniques";i:2;s:28:"Iterative Prompt Development";i:3;s:71:"Using Prompts for Different AI Tasks (Summarization
Hands-On with AI Tools
  • DALL-E
  • GPT-4
  • etc.)";i:1;s:32:"Practical Exercises and Examples";i:2;s:24:"Building Custom Chatbots";i:3;s:24:"Automating Tasks with AI";}
  • a:4:{i:0;s:52:"Working with AI Tools (ChatGPT
AI Ethics and Responsible AI
  • a:4:{i:0;s:28:"Ethical Considerations in AI";i:1;s:30:"Bias and Fairness in AI Models";i:2;s:29:"Privacy and Security Concerns";i:3;s:41:"Guidelines for Responsible AI Development";}
AI Integration and Deployment
  • a:4:{i:0;s:32:"Integrating AI into Applications";i:1;s:21:"Deployment Strategies";i:2;s:37:"Monitoring and Maintaining AI Systems";i:3;s:41:"Case Studies of Successful AI Deployments";}
Advanced Topics in AI
  • a:4:{i:0;s:22:"Reinforcement Learning";i:1;s:38:"Generative Adversarial Networks (GANs)";i:2;s:21:"AI in Computer Vision";i:3;s:27:"AI for Predictive Analytics";}
Case Studies and Projects
  • a:3:{i:0;s:20:"Real-World Use Cases";i:1;s:29:"Guided Projects and Exercises";i:2;s:32:"Q&A and Troubleshooting Sessions";}

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