Live Online Training

AI Utility Tools & Prompt Engineering

Live Online Training H1: AI Utility Tools & Prompt Engineering Course Subhead: Master 30+ powerful AI tools and prompt engineering techniques to automate work, create amazing content, boost productivity, and stay ahead in the AI revolution. No coding or technical background required.

Live Online Training

30+ AI Tools

No Coding Required

Industry Certificate

Trusted by Learners & Professionals from Top Companies

WHY LEARN AI TODAY?

Work Smarter with AI, Not Harder

WHAT YOU'LL LEARN

ChatGPT Mastery

Prompt Engineering

AI Content Creation

AI Image Generation

AI Video Creation

Automation Workflows

Business Productivity

AI Marketing

AI TOOLS YOU'LL MASTER

ChatGPT

The most widely used general-purpose AI assistant

Claude

Anthropic's model for long-form reasoning and analysis

Gemini

Google's multimodal assistant integrated with Workspace

Midjourney

The industry standard for AI image generation

Runway ML

Professional AI video generation and editing

Leonardo AI

Creative-focused image generation for branding

Perplexity AI

AI-powered research and citation-backed answers

Gamma

AI presentation and document creation

ElevenLabs

Studio-quality AI voice generation

HeyGen

AI video avatars for marketing and training

Notion AI

AI built into your notes, docs, and workflows

Canva AI

AI design tools for social media and marketing

COURSE CURRICULUM

01

02

03

04

05

Week 1

AI Foundations

Week 2

ChatGPT & Prompt

Week 3

Content Creation

Week 4

Image Generation

Week 5

AI Video & Voice

What You Will Learn

The Twelve-Week Curriculum

The curriculum is organized into four progressive modules, each building on the previous one. Sessions blend instruction, live demonstrations, supervised practice, and discussion of real workplace use cases.

01

Module 1

The Modern AI Landscape

Before learning how to use generative AI well, learners need an accurate mental model of what these tools actually are. This module covers the territory in plain language: what a large language model is and is not, how it generates text one token at a time, why it sometimes confidently states things that are wrong (and how to spot it), the differences between major model families (the GPT series, Claude, Gemini, Llama, Mistral), and what each one is genuinely good at.

Learners also map out the broader generative AI ecosystem beyond chat — image generation tools like Midjourney and DALL·E, transcription tools like Whisper-based services, research tools like Perplexity, document tools like NotebookLM, and the rapidly growing field of AI-native productivity software. The goal is not memorization but orientation: by the end of Module 1, learners can read AI news critically and make informed choices about which tool fits a given task.

You will Explore

LLMs & How They Work

All AI Families

AI Ecosystem

Top AI Tools Overview

02

Module 2

Prompt Engineering as a Craft

This is the heart of the course and where the most class time is spent. Prompt engineering is treated as a structured skill that can be learned, practiced, and improved measurably. Topics covered include:

Every concept is taught against real exercises. Learners write prompts for drafting customer emails, summarizing meeting notes, restructuring messy spreadsheet data into clean tables, generating first drafts of reports, producing comparison analyses, and many other workplace scenarios. Each exercise is reviewed in class, with discussion of what worked, what did not, and why.

03

Module 3

Generative AI Tools in Practice

This module moves from prompt theory to applied tool use. Learners work hands-on with ChatGPT, Claude, Microsoft Copilot, Gemini, and a rotating selection of specialized tools that are most relevant to their roles. The emphasis is on workflow fit — knowing when to reach for which tool — rather than promoting any single platform.

ChatGPT

MS Copilot

Gemini

More AI tools

Specific topics include using AI for writing and editing across formats (emails, reports, proposals, presentations), AI-assisted research and information synthesis, working with documents and PDFs through AI tools, generating and refining images for business contexts, transcription and meeting summary workflows, and an introduction to no-code AI automation using accessible platforms.

Learners also build personal AI workflows during this module — repeatable, tested sequences of prompts and tools that handle recurring tasks in their actual job. By the end of Module 3, every learner has at least three working workflows they can take back to their team on Monday morning.

Practical Areas

Writing & Editing Across Formats

Research & Information Synthesis

Documents & PDFs with AI Tools

Image Generation for Business

Transcription & Meeting Summaries

No-Code AI Automation

04

Module 4

Responsible AI Use and Business Application

The final module addresses the questions that determine whether AI use is sustainable in a professional context. How do you handle confidential information when working with AI tools? How do you spot and correct AI errors and hallucinations? When is AI output reliable enough to send, and when does it need a human edit? What are the bias and fairness considerations in AI-assisted hiring, evaluation, and customer-facing communication?

Data Privacy & Security

Accuracy & Hallucinations

Human-in-the-Loop Best Practices

Bias, Fairness & Ethical Use

Learners also complete a capstone project during these final weeks: a real workplace use case, planned and built using the techniques from the full course, presented in the final session. Capstones from past cohorts have included AI-assisted sales proposal generators, customer support knowledge bases, internal newsletter production workflows, and recruitment screening assistants.

Capstone Project

Plan • Build • Present

A real workplace AI solution using everything you’ve learned.

By the end of 12 weeks, you won't just use AI — you'll use it strategically, responsibly, and confidently in your everyday work.

REAL-WORLD PROJECTS

AI Blog Generator

Build a complete AI-powered blogging system.

Social Media Campaign

Create engaging posts, graphics, and captions.

AI Presentation Creator

Generate professional presentations.

Marketing Automation

Automate lead generation, emails, and campaigns.

Personal AI Assistant

Build your own AI assistant for work and business.

Course Format and Delivery

The course is delivered fully online through live, instructor-led sessions. There are no pre-recorded video lectures substituted for live instruction — every session is taught live by a working AI practitioner, with real-time questions, demonstrations, and supervised practice.

01

Schedule

Two live sessions per week over twelve weeks, scheduled in evening and weekend slots to accommodate working professionals across US time zones.

02

Recordings

Every session is recorded and made available within 24 hours for learners who miss a class or want to review.

03

Cohort Interaction

Class sizes are kept small enough that every learner gets direct instructor interaction. A cohort discussion space stays active throughout the program for questions between sessions.

04

Practice Exercises

Each module includes structured exercises that are reviewed in the following session. Plan for approximately three to five hours per week of practice outside of live sessions.

05

Capstone

A real workplace AI workflow, designed and built across the final two weeks and presented in the final session.

Prerequisites and Technical Requirements

There are no academic or technical prerequisites. Learners need:

Comfort using a web browser, email, and basic productivity software (Google Workspace, Microsoft 365, or similar)

A laptop or desktop computer with a current operating system and a stable internet connection

A willingness to spend three to five hours per week on practice outside of live sessions

Optional but recommended: a free account with at least one major AI chat tool (ChatGPT, Claude, or Gemini) before the first session

Why Prompt Engineering Skills Matter in the US Job Market

High Demand. Real Impact.

The economic value of AI fluency has moved from theoretical to measurable. Multiple US employer surveys over the past eighteen months have shown that employees with strong generative AI skills complete certain categories of knowledge work significantly faster than peers and produce higher-quality results that managers rate as better or comparable.

More Visibility. Faster Progression.

For most professionals, the impact is not a job change. It is a productivity multiplier within their existing role that translates into visibility, faster progression, and a stronger position in performance reviews.

Future-Ready Advantage.

Learners who move into AI-adjacent roles — AI specialist positions in marketing teams, prompt engineering roles at larger employers, AI training and adoption roles inside companies — leave with a clear sense of how those paths work and what additional skills they would need to develop.

Learn From Industry Leaders

Michael Anderson

Lead Instructor — AI & Cloud

Senior AI engineer with extensive experience designing machine learning platforms and deploying enterprise AI solutions.

David Miller

Cloud & MLOps Instructor

Cloud Architect specializing in scalable AI infrastructure, MLOps automation, and multi-cloud deployments for enterprise.

Industry Recognized Certificate

Receive an industry-recognized certificate after successful course completion.

Career Impact

Increase in productivity
0 %
Hours saved every week
0 +
Higher demand for AI-skilled professionals
0 x
Career opportunities
0 +

What Our Learners Say

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Frequently Asked Questions

No. This course is specifically designed for non-technical learners. No programming is taught, and no programming knowledge is assumed.

Three differences matter. First, the curriculum is structured and progressive — each session builds on the previous one, which a collection of unrelated videos cannot do. Second, it is live and interactive — learners get their actual prompts reviewed and their actual questions answered by a working practitioner. Third, it is accountable — exercises, capstone, and certificate create the structure that turns intention into actual skill.

Every session is recorded and made available within 24 hours. The recommendation is to attend at least 75 percent of sessions live to get the full benefit of the interactive format, but the course is structured so that occasional absences can be made up through recordings.
The course covers the major general-purpose tools (ChatGPT, Claude, Gemini, Microsoft Copilot) and a rotating selection of specialized tools for writing, research, image generation, transcription, and workflow automation. Specific tools are updated each cohort to keep pace with a rapidly changing landscape.

Yes, and that is the explicit design goal. Exercises and capstone projects are built around real workplace use cases, and most learners report applying new techniques to their job within the first three weeks of the course.

It is designed to be. The cohort typically includes a wide range of ages and professional backgrounds. The teaching style is paced for adult learners who are returning to structured study and assumes no recent academic or technical background.
For most learners, the more accurate framing is that it makes them more effective in their current role and creates internal advancement opportunities. For learners specifically targeting AI-adjacent roles, the course is the right starting point but is typically combined with additional specialization — Python for AI & Data Science, Generative AI & LLM, or the AI Full Career Track Bundle — depending on the target role.
Learners are invited into a graduate community that stays active across cohorts, with periodic alumni sessions on new tools and techniques as the field evolves. Many graduates continue into one of the deeper Mindvex tracks within six to twelve months of finishing this course.

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