Mastering Generative AI through OpenAI Hands-On

Learn how artificial intelligence uses data and algorithms to build machine learning models—supervised, unsupervised, and reinforcement—covering regression, classification, clustering, time series, and the data science process.

Explore supervised and unsupervised learning, including regression, classification, and clustering, and learn the six-step machine learning process from objective definition to model evaluation.

Learn how to preprocess data for regression, classification, and clustering by handling missing values, encoding categorical features, addressing outliers, and scaling with min-max or z-score normalization.

Explore how generative AI and large language models power text and content creation, from GPT and ChatGPT to GANs and foundation models, using transformers and training on massive data.

Define and contextualize GPT, a generative pre-trained transformer that generates human-like text via a transformer with self-attention, unsupervised pre-training, and task-specific fine-tuning for applications like chatbots and content generation.

Explore OpenAI models, including GPT variants, ChatGPT and Dolly, and learn to use the OpenAI API for text and image generation, translation, coding, and instruction following.

Learn how to call the GPT API from a Python program, obtain an API key, install the OpenAI package, configure the key, and perform text generation or translation using completions.

Explore the OpenAI playground and ChatGPT differences through a web-based interface, interact with GPT-3.5 turbo and GPT-4, and master temperature, max length, top_p, and penalties.

Explore how ChatGPT architecture drives human-like responses through GPT 3.5/4, transformer models, tokens, and attention, with unsupervised pre-training and RLHF for dialogue.

ChatGPT delivers context-aware language translation that surpasses word-for-word tools, with Portuguese examples, Brazil vs Portugal nuances, and pronunciation tips.

Master generative ai techniques to generate and rearrange lists, add publication years, and explore topics like explainable ai, ethical ai in healthcare, climate change, and quantum ai.

Explore how ChatGPT generates lists of pros and cons, including dietary tradeoffs, environmental and ethical considerations, health impacts, and how to tailor choices with professional guidance.

Learn how to obtain topic quotes with ChatGPT, including time management quotes and author attribution, and use it to generate chapter titles and related quotes for a book.

Use ChatGPT to access and summarize AR/VR research in IT operations and maintenance, with data limited to 2021 and sources such as ResearchGate, IEEE Xplore, and ACM Digital Library.

Explore how to obtain constructive feedback on your content with ChatGPT, starting with positives, then improvements, including counter-arguments, real-world examples, and ethical use in drafting sections.

Explore role playing with ChatGPT to practice language conversations, take on a fruit seller or interviewee role, and receive feedback to improve conversation skills.

Learn to use ChatGPT as a mentor to brainstorm ideas for photography, videography, and gaming ventures, then explore competitors and get step-by-step startup guidance on stock photography platforms like Unsplash.

Learn how ChatGPT and advanced language models enhance presentation design by generating dynamic slide content, integrating into popular tools, and automating outlines, visuals, and export to PowerPoint.

Generate sample data for an online retail business using ChatGPT, then import a pipe-delimited CSV into Excel, clean extraneous rows and columns, and prepare data for building dashboards.

Discover how to guide ChatGPT with prompts for writing, education, translation, and problem solving using prompt engineering to tailor responses, including a Goa, India travel plan example.

Explore retrieval augmented generation (rag) and how combining vector databases, embeddings, and external sources enhances generation accuracy, timeliness, and contextually relevant responses.

Scale product description generation for thousands of e-commerce items by integrating an Excel-based prompt workflow with the OpenAI API, auto-writing descriptions and saving them back to the file.

Generate synthetic data for demand forecasting with generative AI, using a defined demand data schema, Excel templates, and LangChain OpenAI workflows to create realistic, privacy-safe data.

See how generative AI manages inventory data from a csv using a streamlit app and a langchain csv agent, enabling prompts-based data analysis without sql or python.

Develop a structured generative AI roadmap by aligning vision with business goals, assessing current capabilities, selecting models and data strategies, and planning deployment, monitoring, and governance.