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The Complete Prompt Engineering for AI Bootcamp (2026)

Master GPT-5, Claude, Gemini, Midjourney & Veo3 — Build 20+ Real Projects, Write Production-Grade Prompts & Launch Your AI Career

22 Chapters
221 Lessons
1510 min total
Open Access

## The Complete Prompt Engineering for AI Bootcamp (2026) Stop watching AI demos and start building real products. This comprehensive bootcamp teaches you **prompt engineering from fundamentals to production** — coverin...

What you'll learn

  • Introduction
  • Five Principles of Prompting
  • How Does AI Work?
  • Deep Dive on ChatGPT & GPT-5
  • Standard Text Model Practices
  • OpenAI Features & Functionality — Coding

+ 16 more chapters below

Engr Mejba Ahmed

Engr. Mejba Ahmed

Course Instructor

The Complete Prompt Engineering for AI Bootcamp (2026)

About This Course

The Complete Prompt Engineering for AI Bootcamp (2026)

Stop watching AI demos and start building real products. This comprehensive bootcamp teaches you prompt engineering from fundamentals to production — covering every major AI model, framework, and technique you need to work professionally with AI in 2026.

You will build 20+ real-world projects spanning text generation, image creation, video production, AI agents, and production Python applications. Every lesson is designed to give you skills you can apply immediately at work or in your own business.

What Makes This Course Different

  • Multi-model mastery — Learn GPT-5, Claude, Gemini, Midjourney, Veo3, DALL-E 3, and more. Understand each model's strengths so you always pick the right tool.
  • Five Principles framework — A systematic approach to prompting that produces professional-grade output every time, not random trial and error.
  • Production Python coding — Go beyond the chat interface. Build real applications with the OpenAI API, LangChain, LangGraph, embeddings, RAG systems, and autonomous agents.
  • Image + Video generation — Master Midjourney v6, advanced image techniques, and Google Veo3 for AI video creation.
  • Prompt optimization & evals — Learn how professionals measure, test, and improve prompt quality at scale.

What You Will Learn

  • Master the Five Principles of Prompting for consistent, professional results
  • Understand how AI models actually work — tokens, reasoning, hallucinations
  • Use ChatGPT and GPT-5 features like Deep Research, Vision, Canvas, Agent Mode, and Custom GPTs
  • Write production Python code with the OpenAI API — structured outputs, streaming, tool calling
  • Build RAG systems with vector databases, embeddings, and hybrid retrieval
  • Create autonomous AI agents that use tools, plan multi-step tasks, and self-correct
  • Master LangChain and LangGraph for complex AI application architectures
  • Complete 20+ hands-on projects — from summarization to full SaaS features
  • Generate professional images with Midjourney v6, DALL-E 3, and advanced techniques
  • Create AI video content with Google Veo3
  • Optimize prompts with systematic evaluation and testing frameworks
  • Build agent architectures — routing, parallelization, orchestration

Who This Course Is For

  • Professionals who want to use AI effectively in their daily work
  • Developers looking to build AI-powered applications with Python
  • Marketers & creators who need to generate high-quality text, images, and video
  • Career switchers targeting AI Engineer, Prompt Engineer, or AI Product roles
  • Business owners who want to automate workflows and create AI products

Career Impact

Prompt engineering skills are among the most in-demand capabilities in 2026. Professionals who can reliably get production-quality output from AI models command significant salary premiums and unlock entirely new career paths. This course gives you the complete skillset.

Course Curriculum

22 chapters 221 lessons 1510 min

4 lessons available to preview

1 Welcome to the Course
Preview 2min
2 What Is Prompt Engineering?
Preview 5min
3 Accessing Course Resources and Prompts
1min
4 Coding vs Non-Coding Tracks Explained
1min
5 The AI Prompt Toolkit — 700+ Ready-Made Prompts
1min
6 Setting Up Your GitHub Repository
1min
7 The AI Resource Hub
1min
8 Curriculum Overview and Learning Path
2min
1 Give Clear Direction
5min
2 Specify Your Output Format
Preview 5min
3 Provide Reference Examples
5min
4 Evaluate and Iterate on Quality
6min
5 Divide Complex Tasks Into Steps
5min
6 Applying the Five Principles — Worksheet and Cheat Sheet
11min
1 What Are Tokens and Why They Matter
5min
2 Chat Models vs Reasoning Models
6min
3 Understanding and Preventing AI Hallucinations
4min
1 What Is ChatGPT and How Has It Evolved
5min
2 Prompting ChatGPT Effectively
2min
3 Capabilities, Limitations, and When to Use Alternatives
1min
4 ChatGPT Search — Real-Time Web Results
3min
5 Deep Research Mode — Multi-Source Analysis
4min
6 Data Analysis — Upload and Query Any Dataset
3min
7 Image Generation Inside ChatGPT
3min
8 Adding Files and Documents to Conversations
2min
9 Agent Mode — Autonomous Multi-Step Tasks
8min
10 Custom Instructions for Persistent Personalization
1min
11 Keyboard Shortcuts and Power User Tips
1min
12 Canvas — Collaborative Writing and Code Editing
5min
13 Memory — Teaching ChatGPT Your Preferences
2min
14 Projects — Organizing Work Into Persistent Workspaces
4min
15 Scheduled Tasks and Recurring Automations
2min
16 Vision — Analyzing Images and Screenshots
2min
17 The Vision Prompting Guide — Getting Accurate Image Analysis
14min
18 Desktop Application — Workflows Beyond the Browser
5min
19 ChatGPT Atlas — Navigating the Knowledge Graph
1min
20 Study and Learn Mode — AI-Powered Education
2min
21 Group Chats — Multi-Model Conversations
1min
22 GPT Store — Building and Publishing Custom GPTs
9min
1 Role Prompting — Setting the AI's Persona
2min
2 Controlling Output Formats — JSON, Markdown, Tables, and More
5min
3 Least to Most Prompting — Breaking Down Complexity
2min
4 Explain Like I'm Five — Simplifying Complex Topics
2min
5 Meta Prompting — Asking AI to Write Its Own Prompts
3min
6 Overcoming Maximum Token Output Length
2min
7 Sentiment Analysis With Text Models
2min
8 Writing Clear Instructions — Detailed and Specific
1min
9 Writing Clear Instructions — Specifying Sequential Steps
1min
10 Writing Clear Instructions — Using Delimiters Effectively
3min
11 Writing Clear Instructions — Controlling Response Length
1min
12 Asking for Context Before Answering
4min
13 Pre-Warming Conversations for Better Results
4min
14 Working Around Token Limits in Long Conversations
2min
15 Prompt Injection — Understanding and Defending Against Attacks
5min
1 OpenAI Platform Overview and Key Features
4min
2 Setting Up an OpenAI Account and API Key
1min
3 Using the OpenAI Playground to Test Prompts
5min
4 Responses API — Sending Messages Programmatically
6min
5 Coding Notebook — Working With Different OpenAI Services
14min
6 Counting Tokens With tiktoken
13min
7 Managing Message History and Context Windows
10min
8 What Is Streaming and Why It Matters
4min
9 Rate Limits — Retrying and Handling Throttled Requests
5min
10 Chat Completions vs Responses API — When to Use Which
4min
11 What Are Structured Outputs and Why They Matter
3min
12 Structured Outputs in Practice — Enforcing JSON Schemas
7min
13 Understanding Tool Calling — Connecting AI to External Functions
5min
14 Tool Calling in Practice — Building Function-Connected Prompts
9min
15 Building a Simple Agent With Tools
7min
16 Parallelizing Requests With Async OpenAI
10min
1 Introduction to Retrieval — Why Context Matters
22min
2 Understanding Vector Embeddings — Turning Text Into Numbers
8min
3 Retrieval Augmented Generation (RAG) With Vector Databases
13min
4 RAG With Supabase PGVector — Production-Grade Setup
17min
5 Hybrid Retrieval — Combining SQL Filtering and Embeddings
10min
6 How to Evaluate Retriever Quality
13min
7 Extra Notebooks for Advanced Users
1min
1 AI Agents and Workflows — Architecture Overview
5min
2 Multi-Source Customer Support Agent
23min
3 Introduction to the OpenAI Agents SDK
15min
4 Exercise — Blog Post Generator Agent Workflow
7min
1 Role Prompting in Production Code
5min
2 Few-Shot Learning — Teaching by Example
Preview 7min
3 Emotion Prompting — Leveraging Affective Cues
4min
4 Chain of Thought — Step-by-Step Reasoning
7min
5 Self-Consistency Sampling — Majority Vote Reasoning
5min
6 Reason and Act (ReAct) — Combining Thinking With Tools
7min
7 Personas of Thought — Multi-Perspective Problem Solving
11min
8 Prompt Optimization — Systematic Improvement Techniques
9min
9 What Is Prompt Caching and When to Use It
2min
10 Prompt Caching in Practice — Reducing Latency and Cost
4min
11 OpenAI Realtime API — Building Voice-Enabled AI
4min
1 What Is LangChain and Why It Exists
3min
2 Installation and Environment Setup
3min
3 Chat Models — Connecting to Multiple Providers
6min
4 Chat Prompt Templates — Dynamic Prompt Construction
4min
5 Streaming Responses in LangChain
2min
6 Output Parsers — Structured Data From LLM Responses
8min
7 Summarizing Large Amounts of Text
5min
8 Document Loaders and Text Splitting Strategies
4min
9 Tagging Documents With AI Classification
3min
10 LCEL — The Runnable Protocol Explained
10min
11 LCEL — Chat Models, Itemgetter, and RAG Chains
8min
12 LCEL — Chat Message History and Memory
7min
13 LCEL — Creating Multiple Chains
2min
14 LCEL — Conditional Logic, Branching, and Merging
7min
15 LangChain Vector Databases and the Indexing API
9min
16 LCEL Configurable Fields — Runtime Chain Customization
5min
17 LangChain Agents and Tools — Autonomous Task Execution
15min
1 What Is LangGraph and When to Use It Over LangChain
3min
2 State, Nodes, and Edges — Core Graph Concepts
8min
3 Building Your First LangGraph Workflow
10min
4 Conditional Routing and Dynamic Graph Paths
8min
5 Tool Integration in LangGraph Agents
9min
6 Human-in-the-Loop — Adding Approval Steps
7min
7 Subgraphs and Hierarchical Agent Design
8min
8 Persistence and Checkpointing — Resumable Workflows
9min
9 Production Deployment Patterns for LangGraph
7min
1 Project — Progressive Summarization Pipeline
1min
2 Project — AI Comedy Writer
2min
3 Project — Complete eBook Generator
3min
4 Project — SEO Blog Article Writer
4min
5 Project — Thought Leadership Post Generator
5min
6 Project — Product Requirements Document Writer
6min
7 Project — News Story Summarizer
7min
8 Project — Book Summarization Engine
8min
9 Project — Review Classification System
9min
10 Project — Text to Speech With OpenAI
10min
11 Project — Running LLMs Locally With LangChain and LMStudio
11min
12 Project — YouTube Video Transcription Pipeline
12min
13 Project — Fine-Tuning a Writing Style Model
13min
14 Project — Social Media Content Scheduler
14min
15 Project — Reverse Engineering a Publication Style
15min
16 Project — Building a GPT Wrapper With Flask and HTMX
16min
17 Project — Qualitative Research Analysis Tool
17min
18 Project — Claim Detection and Fact-Checking Pipeline
18min
19 Project — OpenAI Realtime Voice Assistant With Twilio
19min
20 Project — Automating Product Descriptions With GPT-V
20min
21 Project — UX Landing Page Analyzer With GPT-V
21min
22 Project — Memetic Analysis With GPT-V
22min
1 What Is Midjourney and How It Compares to Other Image Models
1min
2 Getting Started — Discord Setup and First Generations
2min
3 Understanding Midjourney Parameters and Aspect Ratios
3min
1 The Anatomy of an Effective Image Prompt
1min
2 Style Descriptors — Photorealistic, Illustration, Painterly
2min
3 Lighting and Mood — Controlling Atmosphere
3min
4 Camera Angles and Composition Techniques
4min
5 Color Theory for AI Image Generation
5min
6 Subject Descriptions — Specificity That Gets Results
6min
7 Background and Environment Control
7min
8 Negative Prompting — Excluding Unwanted Elements
8min
9 Consistency Across Multiple Generations
9min
10 Upscaling and Post-Processing Best Practices
10min
11 Building a Personal Image Prompt Library
11min
1 Multi-Subject Scene Composition
1min
2 Text Rendering in AI Images
2min
3 Artistic Style Transfer and Blending
3min
4 Photorealistic Portrait Generation
4min
5 Product Photography and Mockup Creation
5min
6 Architectural and Interior Design Visualization
6min
7 Character Design and Consistency Across Frames
7min
8 Infographic and Data Visualization Generation
8min
9 Logo and Brand Identity Concept Generation
9min
10 Fashion and Clothing Design With AI
10min
11 Food Photography and Styling With AI
11min
12 Landscape and Nature Scene Generation
12min
13 Abstract Art and Creative Expression
13min
14 Combining AI Images With Real Photography
14min
15 Batch Generation Workflows for Content Teams
15min
16 Ethical Considerations in AI Image Generation
16min
1 Project — Social Media Visual Content Calendar
1min
2 Project — Complete Brand Identity Kit
2min
3 Project — Children's Storybook Illustrations
3min
4 Project — Product Catalog Visualization
4min
5 Project — Real Estate Listing Enhancement
5min
6 Project — Educational Infographic Series
6min
7 Project — Personal Portfolio Art Collection
7min
1 Why Prompt Optimization Matters at Scale
10min
2 Defining Quality Metrics for Your Use Case
15min
3 Building Evaluation Datasets — Gold Standards and Edge Cases
20min
4 Manual Evaluation Frameworks — Rubrics and Scoring
15min
5 Automated Evaluation With LLM-as-Judge
20min
6 A/B Testing Prompts — Statistical Significance in Practice
18min
7 Temperature, Top-P, and Parameter Tuning
15min
8 Prompt Versioning and Change Management
12min
9 Cost Optimization — Same Quality, Lower Spend
20min
10 Latency Optimization — Faster Response Times
15min
11 Regression Testing — Catching Prompt Degradation
20min
12 Building a Prompt Optimization Pipeline From Scratch
35min
1 Prompt Chaining — Sequential Multi-Step Pipelines
7min
2 Routing — Dynamic Model and Prompt Selection
7min
3 Parallelization — Running Multiple AI Calls Concurrently
5min
4 LLM Orchestrators — Managing Complex AI Workflows
7min
5 Autonomous Agents — Self-Directed Task Completion
10min
6 Mixture of Experts — Aggregating Multiple Model Outputs
3min
7 Evaluator-Optimizer — Self-Improving Agent Loops
15min
8 Additional Agent Architecture Patterns
2min
1 What Is Google Veo3 and How It Changed AI Video
3min
2 Getting Started — Access, Interface, and First Generation
3min
3 Crafting Effective Video Prompts — Structure and Timing
3min
4 Camera Movement and Cinematic Techniques
3min
5 Character and Scene Continuity Across Clips
3min
6 Audio Integration and Soundtrack Matching
3min
7 Building Complete Video Projects With Veo3
4min
1 DALL-E 3 Capabilities and Unique Strengths
4min
2 Text Rendering and Typographic Control in DALL-E 3
4min
3 DALL-E 3 vs Midjourney vs Flux — Choosing the Right Tool
3min
1 Google Gemini — Multimodal AI Powerhouse
2min
2 Gemini 2.0 Native Image Generation
3min
3 Google Gemini Deep Research — Comprehensive Analysis
4min
4 Meta LLaMA — Open-Source Foundation Models
5min
5 Runway ML — AI Video Editing and Generation
4min
6 Google Vision API — Image Understanding at Scale
3min
7 OpenAI Whisper — Speech Recognition and Transcription
2min
8 Testing and Comparing Open-Source Models
12min
9 Flux — Fast Image Generation With Diffusion Models
4min
10 Google NotebookLM — AI Research and Study Tool
6min
11 Groq Cloud — Ultra-Fast LLM Inference
4min
1 Course Recap — Key Takeaways and Framework Summary
3min
2 Building Your AI Portfolio and Career Path
2min
3 Continuing Your AI Journey — Resources and Community
2min
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