Prompt Engineering Techniques

Overview

Program Description

In this course, students will uncover the intricacies of crafting prompts that optimize interaction with Large Language Models (LLMs), a coveted skill in today’s tech-centric landscape. They will explore techniques for enhancing chatbot memory and navigating vector search strategies and databases. The course will serve as a comprehensive roadmap to mastering prompt engineering, empowering you to elicit meaningful responses from LLM applications and tackle prompt hacking challenges. With these proficiencies, students will adeptly craft compelling prompts for LLMs and proficiently analyze vector search outcomes, preparing for impactful roles in the AI and machine learning sector.

40 hours / 2 Weeks

Certificate

In-Class, Distance, Combined

Learning Objectives / Outcomes

Upon successful completion of this program, the student will have reliably demonstrated the ability to:

  • Understand the prompts
  • Create effective prompts
  • Utilize open AI at various platforms
  • Work with open AI and google bard

Career Occupation

Career options available but not limited to:

  • AI Research Assistant
  • AI Research associate consultant
  • AI Analyst Trainee

Admission Requirements

To be eligible for admission, applicants must meet the following criteria:

Basic Admission Requirements 

  • High School Completion: Applicants must have a high school diploma or an equivalent qualification.
  • Age Requirement: Minimum 19 years of age. 
  • Mature Student Status*: Applicants who have not completed high school and are at least 19 years of age, may apply as a mature student. 

*Mature student status may be granted to applicants who are over 19 years old and have not completed secondary school or equivalent. The applicants will be considered for admission based on the skills and experience they have acquired since leaving school. The applicant is required to provide the most recent transcripts or proof of academic accomplishments, a resume or summary of professional accomplishments, and two letters of recommendation from both their current and previous employers. The applicant may be interviewed by the Registrar’s or Academic office to further assess their suitability for admission to the program of study.

Methods Of Evaluation

Students demonstrate their learning in the following ways:

Evaluation Method Weight
Assignment 1 25%
Assignment 2 25%
Final Project/Exam 50%
Total 100%

Completion Requirements

 To successfully complete the program, students must meet ALL of the following requirements:

  • Maintain a minimum attendance rate of 80% 
  • Achieve a minimum overall score of 70% to successfully pass.

Curriculum

Module Topics
1 Introduction to Prompt Engineering

  • What is Prompt Engineering?
  • Importance of Prompt Engineering
  • Applications of Prompt Engineering
2 Understanding Prompts

  • Definition and Types of Prompts
  • Components of a Prompt
  • Understanding Prompt Context
  • Problems and Challenges with Prompts
3 What is Prompt Engineering?

  • Eliciting Desired Response
  • Eliciting Desired Response – Hands On
  • Clarity and Specificity in Prompts
4
  • Dealing with Ambiguity
  • Handling Sensitive Topics and Content Safeguards
  • Importance of Context in Prompt Design
5
  • Prompt Strategies for Better Output
  • Useful Prompt Templates
6 Creating Effective Prompts

  • Case Studies: Prompt Engineering Examples
  • Step-by-Step Process of Creating Prompts
  • Prompt engineering for Text Summarization
7
  • Prompt engineering for Information Extraction
  • Prompt engineering for Question Answering
  • Prompt engineering for Text Classification
8
  • Prompt engineering for Code Generation
  • Prompt engineering for Reasoning
  • Analyzing and Evaluating Prompt Performance
9 Working with OpenAI API

  • Overview of OpenAI API
  • ChatGPT PlayGround
  • How to setup ChatGPT add-on?
10
  • Get started with ChatGPT in Google Docs
  • Get started with ChatGPT in Google Sheets
  • Data generation trick for ChatGPT in Google Sheets
11 Advanced Prompt Engineering

  • Harnessing the Power of System Messages and Instructions
  • Dealing with Biases in Prompt Responses
  • Mitigating Inappropriate or Unwanted Responses
12
  • Engineering Prompts for Multilingual and Multicultural Contexts
  • Building Iterative and Interactive Prompt Chains
13 Future of Prompt Engineering and AI Conversations

  • Evolution and Trends in AI Conversational Models
  • Innovations and Opportunities in Prompt Engineering
  • Challenges and Ethical Considerations in Prompt Engineering
14 Working with other popular AI tools

  • Bard
  • Claude

Fee Details

Tuition CAD 950
Application Fee CAD 150
Administration Fee CAD 50
Course Materials CAD 50
Course Retake CAD 850 per course
Copy of Transcript CAD 20 per copy

INTAKES
Start dates:
7 September 2026 | 5 October 2026 | 2 November 2026 | 30 November 2026 | 11 January 2027 | 8 February 2027 | 8 March 2027 | 12 April 2027 | 10 May 2027 | 7 June 2027 | 5 July 2027 | 9 August 2027

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