Prompt Engineering Course on Generative AI for Python Developers

 Generative AI Prompt Engineering Certification Course Overview:

Endtrace Training curriculum features hands-on sessions with real-world scenarios in Generative AI technology. You’ll gain the in-depth knowledge on essential LLM model and techniques needed to excel.

In this Generative AI  Prompt Engineering Certification course covers the comprehensive view of generative AI, with topics including what it is, how it works, how to create your own content, different types of LLM models, future predictions, and more.

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, Llama 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 LLM Fundamentals

• Definition of Prompt Engineering
• Understanding Large Language Models (LLMs)
• Available Large Language Models (LLMs) in the market
• Types of Large Language Models (LLMs)
• Importance of Prompt Engineering in Generative AI

foundational understanding of Generative AI

• Clear definition of Artificial Intelligence (AI)
• Introduction to Generative AI
• Why Learn Generative AI?
• How Generative AI Works?
• The Rise of Generative AI

LLM Model Architecture:

• Understanding Transformer Architecture
• Transformer Model Layers in-depth
• Natural Language Processing (NLP)

Prompt Engineering Models and Techniques

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

Crafting Effective Prompts for LLMs

• Prompt Structuring and Alignment
• Techniques for Prompt Refinement and Fine-Tuning
• Enhancing Prompt Clarity and Specificity

Understand Neural Networks used in LLMs

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

Understand  LLM Model Key Parameters

• Temperature and its settings
• Frequency Penalty
• Presence Penalty
• Top-k
• Top-p
• Stop Sequence

Designing Effective Prompts with Python

• Programming with LLM APIs in Python
• Accessing APIs from OpenAI, Gemini
• API Calls, Rate Limits, and Best Practices
• 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
• 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
• Use Cases: Effective Prompt Engineering in Industry
• Tricking the LLM Model
• Bias the LLM Model

Working with Paid & Open-Source LLMs

• Practice and Play with ChatGPT, GeminI, Copilot.
• Introduction to Open-Source LLMs (e.g., LLaMa, Flan-T5)

Advanced Techniques for AI Interaction

• Leveraging AI Playgrounds for Prompt Testing
• Evaluating and Measuring Prompt Effectiveness
• Debugging and Improving Model Responses

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 knowledge.
• Basic Communication Skills.
• Basic knowledge of LLMs is add-on. (Not Mandatory)

What You’ll Gain from This No-Code Prompt Engineering Course:

Design and Optimize Prompts

• Learn simple tactics to create powerful prompts that boost model performance for tasks like summarization and data extraction.
• Build a Custom Prompt framework to apply advanced techniques without coding in content creation.

Master Essential Prompting Techniques

• Apply the latest methods, like few-shot learning, chain-of-thought, RAG, and more, to real-world scenarios.

Develop Real-World GPTs, AI Agents, No-Code Applications

• Create Custom-GPT, AI Agents.
• Use LLMs with external knowledge to build impactful AI solutions.

Use the Latest Tools in AI Prompting

• Work with tools like ChatGPT Tokens,  Content Chunking, and more.
• Stay up-to-date on trends and the future of prompt engineering—without programming.

Get practical skills to build effective prompts using top LLM applications effortlessly. Ready to upskill?