Unlock the Power of AI: Build Your Personal GPT Assistant

By the end of the course, you will have acquired a solid understanding of the basic concepts and applications of Generative AI and be positioned to continue exploring this groundbreaking field.

We begin with an overview of the fundamentals of artificial intelligence and natural language processing (NLP), ensuring you grasp the scope and power of AI GPT models. With expert guidance, you'll be introduced to the architecture and functioning of these models, breaking down complex topics into digestible and engaging lessons.

Following the theoretical foundation, you will step into practical sessions where you can observe the magic first-hand. We will provide step-by-step instructions on building, training, and deploying a basic AI GPT model using accessible tools and platforms. You'll experiment in a controlled, supportive environment, enabling your creativity to flow and your new skills to solidify.

By the end of the workshop, you will have created your own AI GPT model. 

Learning Objectives:

1. Explore basic concepts of Generative AI and GPT models.
2. Discuss the fundamental principles of NLP in AI.
3. Identify key components and workflows for creating AI GPT models.
4. Set up the environment for building GPT models.
5. Perform data collection and preprocessing for training.
6. Evaluate the quality of generated text and provide feedback.
7. Design and build a basic AI GPT model.
8. Generate original text and explore practical applications.

Topic Outline:
Understanding Generative AI and GPT
- What is Generative AI?
- Basic concepts and real-world applications

Basics of Natural Language Processing (NLP)
- What is NLP?
- Overview of natural language processing and its use in AI
- Key Components of NLP Tokens, tokenization, and preprocessing text data

Hands-On Session: Building Your GPT Model
- Data Collection and Preparation
- How to source and prepare text data for training
- Cleaning and preprocessing your dataset

Training Your GPT Model
- Step-by-step guide to training the model using sample data
- Running the training process and monitoring progress
- Real-time Demonstrations
- Generating text using your trained model

Practical Applications and Use Cases
- Use Cases of GPT Models
- Real-world applications: chatbots, content generation, summarization

Best Practices
- Ethical considerations and responsible use of AI
- Tips for improving model performance
 

Prerequisites
No prior experience in coding or AI is required.