Beginner Artificial Intelligence 24 hours Featured

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

Course Instructor

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Chapters 22

Lessons 221

Duration 24 hours

Level Beginner

Certificate On Completion

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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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The Complete Prompt Engineering for AI Bootcamp (2026)

What you'll learn

Get Full Access

Get Full Access

About This Course

The Complete Prompt Engineering for AI Bootcamp (2026)

What Makes This Course Different

What You Will Learn

Who This Course Is For

Career Impact

Course Curriculum

Introduction

Five Principles of Prompting

How Does AI Work?

Deep Dive on ChatGPT & GPT-5

Standard Text Model Practices

OpenAI Features & Functionality — Coding

Retrieval, Embeddings & Vector Databases — Coding

Building AI Agents — Coding

Advanced Text Model Techniques — Coding

Deep Dive on LangChain — Coding

Deep Dive on LangGraph — Coding

AI Text Model Projects

Deep Dive on Midjourney v6

Standard Image Model Practices

Advanced Image Generation Techniques

AI Image Model Projects

Prompt Optimization & Evals

Agent Architectures — Coding

Deep Dive on Google Veo3

Deep Dive on DALL-E 3

Deep Dive on Other AI Models

Conclusion & Next Steps

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Ratings & Reviews

No reviews yet

Share Your Experience

Continue Learning

Building AI Agents with Claude: From Prompts to Production

How to Build Million-Dollar SaaS Applications Using Claude Code (Opus 4.6 & Sonnet 4.6)

AI Automation with Python: Build 10 Production-Ready Intelligent Systems

Engr Mejba Ahmed

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