Generative AI for Developers freeCodeCamp

• What is the focus of the generative AI course?

  Exploring key concepts of generative AI
• What hands-on projects will be included in the course?

  Text summarization and custom chatbots
• Which tools will be used in the course?

  Hugging Face, OpenAI, and LangChain
• What will students master by the end of the course?

  AI pipelines, vector databases, and deployment techniques
• What platforms will be covered for deployment techniques?

  Google Cloud Vertex AI and AWS Bedrock
• Why is generative AI considered a demandable skill?

  All industries are using generative AI
• What should you know to crack a good job in today's market?

  Knowledge of generative AI
• What does the course cover from basics to advanced concepts?

  Everything needed to master generative AI
• What will be emphasized alongside theoretical knowledge in the course?

  Practical implementation of generative AI
• What will students learn about data pre-processing?

  Techniques for processing data and generating embeddings
• What types of large language models will be covered?

  Commercial and open-source large language models
• What platform will students start with for large language models?

  The Hugging Face platform and its API
• What will students learn about OpenAI in the course?

  About its evolving large language models
• Why is prompt engineering important in generative AI?

  It influences the response from large language models
• What types of vector databases will be mastered in the course?

  Pinecone, Chroma, and others
• What is the purpose of mastering vector databases in the course?

  To create a knowledge base for applications
• What frameworks will be covered for generative AI applications?

  LangChain, LlamaIndex, and others
• What is retrievable augmented generation (RAG)?

  Creating applications with custom data
• What will students learn about fine-tuning in the course?

  How to fine-tune large language models on custom data
• What will students implement at the end of the course?

  End-to-end project implementations with deployment
• What is LLM Ops in the context of generative AI?

  Trending topic for large language model applications
• What platforms will be covered for LLM Ops?

  Bedrock and Vertex AI
• Who is the instructor of the generative AI course?

  BK Ahmed Bui
• What is the instructor's experience in the field?

  More than four years in machine learning
• What will the course provide for beginners?

  A comprehensive understanding of generative AI
• What types of problems will be solved in the course?

  Diverse problem statements related to generative AI
• What is generative AI?

  Generates new data based on training samples
• What types of data can generative models produce?

  Image, text, audio, and video
• How do generative models differ from discriminative models?

  Generative models create new data, discriminative models predict
• What type of data do generative models use for training?

  Unstructured data
• What is the role of prompts in generative AI?

  They guide the model's output generation
• How do generative models learn from unstructured data?

  By understanding patterns in the data
• What is the significance of unstructured data in today's world?

  It is generated in large amounts online
• What can generative models do for content generation?

  Generate code, stories, music, and videos
• How can generative models assist content creators?

  By generating content based on prompts
• How does generative AI relate to real-life learning?

  It learns from vast amounts of data
• Why are generative models important in understanding complex patterns?

  They can analyze large amounts of unstructured data
• What is one application of generative models in content generation?

  Generating complete videos from prompts
• How can generative models assist blog writers?

  By generating blogs based on topics
• What is the potential of generative models in the market?

  They are becoming widely used tools