Section 1: Advanced Prompt Engineering and GPT Usage

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1. Advanced use of ChatGPT with GPT-4 and GPT-4o

2. Multimodal capabilities: text, image, and web browsing

3. Introduction to Custom GPTs

4. Creation and configuration of your own GPTs

5. Connecting GPTs with external services (AiPDF, Canva, Browser)

6. Advanced data analysis with ChatGPT

7. Publishing and sharing GPTs

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Section 2: No-Code Automation with Generative AI

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1. Introduction to no-code automation

2. Project setup and configuration in OpenAI

3. API keys, costs, and free alternatives (Gemini)

4. Introduction to and use of Zapier

5. Creating automated workflows with AI

6. Integrating ChatGPT and Gemini into workflows

7. Building AI agents and chatbots without code

8. Adjusting AI parameters within workflows

9. Publishing and testing agents and bots

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Section 3: Practical Applications of LLMs with APIs and Chatbots

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1. Introduction to Google Colab and testing environments

2. Accessing OpenAI and Google Gemini APIs

3. Automation with ChatGPT: email detection and URL analysis

4. Integrating LLMs with Gmail and other services

5. Creating and deploying advanced chatbots

6. Practical use cases integrating external services

7. Fine-tuning parameters

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Section 4: Architecture and Internal Functioning of LLMs

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1. Introduction to the technical workings of LLMs

2. Recurrent Neural Networks (RNN) and LSTM

3. Transformers: Encoder, Decoder, and Multi-head Attention

4. Embeddings and positional encoding

5. Types of transformers and text generation

6. Evolution of GPT and ChatGPT architecture

7. Practical case: text generation with transformers

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Section 5: Fine-Tuning LLMs and Efficient Adjustment (PEFT)

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1. Introduction to the AI project lifecycle

2. Differences between pretrained and fine-tuned models

3. Preparing datasets for fine-tuning

4. Instruction fine-tuning and performance evaluation

5. Hugging Face and using public models

6. Parameter-Efficient Fine-Tuning (PEFT) and LoRA

7. Practical cases with Flan-T5, GPT, and LLAMA

8. Prompt Tuning and soft prompts usage

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Section 6: Reinforcement Learning with Human Feedback (RLHF)

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1. Introduction to reinforcement learning

2. What is RLHF and why is it useful?

3. Proximal Policy Optimization (PPO)

4. Applying RLHF in practice

5. Practical cases with TinyLLAMA and policy adjustments

6. Evaluating model behavior

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Section 7: Image, Video, and Audio Generation with AI

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1. Introduction to multimodal Generative AI

2. GANs: how they work, discriminator and generator

3. Practical case: video editing with GANs

4. Diffusion models: fundamentals and architecture

5. CLIP and text-to-image generation

6. Hands-on practice with DALL·E 3 and Stable Diffusion

7. Visual AI applications in creative industries

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Section 8: Generative AI for Art with Midjourney

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1. Initial setup of Midjourney

2. Creating artistic images and videos

3. Customizing images and styles

4. Using reference images

5. Advanced prompting in Midjourney

6. Free alternative: AUTOMATIC1111

7. Image generation with AUTOMATIC1111