Generative AI using OpenAI API for Beginners Course Syllabus

Overview: This beginner-friendly course provides a hands-on introduction to building real-world AI applications using the OpenAI API. You'll gain practical experience across text, audio, image, and data retrieval tasks through step-by-step labs and real tools like chatbots, transcribers, and semantic search apps. With a total duration of approximately 6 hours, this course is designed for Python developers looking to quickly integrate generative AI into their workflows.

Module 1: Introduction & Setup

Estimated time: 0.5 hours

• Set up Python and install OpenAI libraries
• Authenticate using OpenAI API keys
• Understand key OpenAI models: GPT, Whisper, and DALL·E
• Configure development environment for API integration

Module 2: Basic API Calls & Prompting

Estimated time: 0.75 hours

• Perform text completions with adjustable parameters
• Handle JSON responses from the API
• Apply best practices for effective prompting
• Manage token usage and decoding strategies

Module 3: Audio with Whisper

Estimated time: 0.75 hours

• Transcribe audio files to text using Whisper
• Translate non-English speech into English
• Integrate transcribed text with other OpenAI models
• Process and handle audio input formats programmatically

Module 4: Image Generation with DALL·E

Estimated time: 1 hour

• Generate images from text prompts using DALL·E
• Edit existing images using inpainting techniques
• Save and retrieve generated images in Python
• Display images dynamically within applications

Module 5: Embeddings & Semantics

Estimated time: 1 hour

• Generate text embeddings using OpenAI models
• Compute similarity scores for semantic search
• Implement document clustering and topic modeling
• Build Q&A and retrieval-based applications

Module 6: Advanced Features & Error Handling

Estimated time: 0.75 hours

• Handle multiple completions and model errors
• Manage context length and token limits
• Use OpenAI’s moderation API to filter unsafe content
• Control response quality and reliability

Module 7: Function Calling & Structured Output

Estimated time: 1 hour

• Use function calling to enable task execution
• Generate structured JSON output from models
• Simulate plugin-like behavior in applications
• Design workflows for structured assistant interactions

Module 8: End-to-End Projects

Estimated time: 1 hour

• Build a functional chatbot with multi-turn conversation
• Create a sentiment analyzer using text classification
• Develop an image-based AI tool combining inputs

Prerequisites

• Basic knowledge of Python programming
• Familiarity with JSON structure and parsing
• Understanding of API concepts (helpful but not required)

What You'll Be Able to Do After

• Integrate OpenAI API into Python applications
• Build tools for text generation, transcription, and image creation
• Implement semantic search and document similarity systems
• Create structured AI workflows using function calling
• Develop end-to-end AI applications combining text, audio, and image inputs