Prompt Engineering Course on Generative AI for Python Developers

GenAI Prompt Engineering Certification Course Topics

Endtrace’s curriculum features hands-on sessions with real-world scenarios in Prompt Engineering. You’ll gain the essential tools and techniques needed to excel.

Are you a Python developer looking to enhance your AI skills? This course is tailored specifically for you.

Large Language Models (LLMs) like ChatGPT, LangChain, and Gemini are transforming industries.

Learn advanced techniques like Zero-Shot, few-shot learning, chain-of-thought prompting, and RAG. Each concept is taught through practical examples designed for Python developers.

Optimize token usage and enhance response times within context window limits by applying chunking methods —skills that employers highly value.

Prompt Engineering Course Outline

Introduction to Prompt Engineering and AI Fundamentals

• Understanding Large Language Models (LLMs)
• The Role of Prompt Engineering in AI
• Ethical Considerations in Prompt Engineering

Introduction to LLM Model Architecture

• Transformer Architecture 
• Traditional Natural Language Processing (NLP)
• Basics of Autoregressive Model

Prompt Engineering Models and Techniques

• Types of Prompt Engineering Models
  • RAG (Retrieval-Augmented Generation)
  • COT (Chain of Thought)
  • ReAct (Reasoning and Action)
  • Zero-shot/Few-shot/Many-Shot Prompting
  • Self-Reflection & Self-Consistency
  • Meta Prompting & Automatic Prompt Engineering

Crafting Effective Prompts for LLMs

• Prompt Structuring Basics
• Techniques for Prompt Refinement
• Enhancing Prompt Clarity and Specificity

Basics of Neural network models used in LLMs

• Basics Recurrent neural networks (RNN)
• Convolutional neural networks (CNN)
• Long short-term memory (LSTM)

Designing Effective Prompts with Python

• Programming with LLM APIs in Python
• Accessing APIs from OpenAI, Anthropic, and others
• API Calls, Rate Limits, and Best Practices
• Error Handling and Optimizing API Usage
• Structuring and Testing Prompts in Python
• Building Reusable Prompt Functions
• Testing and Iterating Prompt Structures
• Version Control and Documentation
• Python-based Tools for Prompt Design
• Streamlit, Jupyter Notebooks, and Python IDEs
• Libraries for Experimentation and Evaluation: transformers, langchain
• Integrating Prompts into Python-based Applications

Practical Applications of Prompt Engineering

• Prompting for Marketing and Content Creation
• Customer Support and User Assistance Prompts
• Scenario-Based Prompting: Real-World Use Cases
• Case Studies: Effective Prompt Engineering in Industry

Certification and Career Development

• Preparing for Global Prompt Engineering Certification
• Career Opportunities in Prompt Engineering

Prerequisites:

• We will explore with no-code tools
• Core Python knowledgeable
• Basic Communication Skills.
• Basic knowledge of LLMs is add-on.

What You’ll Gain from This Prompt Engineering Course for Python Developers:

Design & Optimize Powerful Prompts

Learn techniques to craft high-impact prompts for tasks like summarization, data extraction, and more. Create effective frameworks for advanced prompts—without needing extra code.

Master Essential Prompting Skills

Apply leading methods like few-shot learning, chain-of-thought, and RAG to real-world challenges. Use tools like ReAct and function calling to build smarter, AI-powered applications.

Build Real-World, No-Code Solutions

Develop practical AI solutions like custom chatbots, tagging systems, and product review analyzers. Leverage LLMs with external data sources for high-impact applications.

Evaluate & Enhance AI Quality

Measure key metrics in AI performance, safety, and reliability. Address crucial safety topics, including prompt injection and moderation.

Stay Current with Top AI Tools

Gain hands-on experience with ChatGPT, Llama Index, and LangChain. Stay at the forefront of prompt engineering—no extra programming needed.