Prompt Engineering Training
The main goal of prompt engineering training is to teach people how to create, improve, and hone prompts for AI models—specifically in large language models (LLMs) and natural language processing (NLP). The training covers techniques for creating efficient input queries that will enable AI systems to produce precise, contextually accurate, and pertinent outputs. Participants gain experience interacting with ChatGPT and other AI models, honing them for various use cases in customer service, healthcare, and finance sectors.
- 10+ Courses
- 30+ Projects
- 400 Hours
Prompt Engineering Training is suitable for the following target audiences:
Developers and AI Enthusiasts: This course is appropriate for developers and AI enthusiasts who wish to focus on developing efficient prompts for AI models, increasing their productivity in generating desired results.
Data Scientists and Machine Learning Engineers: Professionals working with AI systems that need to hone their prompt engineering abilities to maximize model performance, lower errors, and enhance user interactions are best suited as data scientists and machine learning engineers.
Content Creators and Marketers: The target audience consists of professionals in marketing, customer service, and content production who want to use AI tools for automation, content development, and improving customer interaction.
Company Analysts and Consultants: Ideal for those who wish to use AI to drive company strategies through fast engineering methodologies, enhancing automation solutions and decision-making processes.
Prompt Engineer: In charge of creating and refining prompts to communicate with AI models across various industries, guaranteeing that AI systems produce precise and pertinent outcomes.
AI Consultant: Assisting companies in implementing AI solutions by creating efficient workflows and prompts, increasing automation, and boosting business results.
Specialist in Natural Language Processing (NLP): Using prompt engineering to enhance AI’s comprehension of human language to enable more precise and efficient NLP applications.
AI Product Manager: Supervising the incorporation of AI technology and timely optimization into goods and services while ensuring they complement corporate objectives.
Expert in Content Automation: Applying AI technologies to create content and streamline customer support, marketing, and digital media procedures via efficient fast engineering.
As more industries embrace AI-driven solutions, there is a growing need for qualified quick engineers and associated positions in both the USA and Canada. These positions offer attractive pay and opportunities for advancement.
- Agile Overview
- Agile Manifesto & Principles
- Agile vs. Traditional (Waterfall) Approaches
- Scrum, Kanban, XP – overview of frameworks
- Role of a Business Analyst in Agile BA responsibilities in Agile teams
- Collaboration with Product Owner, Scrum Master, Dev Team
- Scrum Deep Dive
- Roles, Events, Artifacts
- Product Backlog, Sprint Planning, Review, and Retrospective
- Kanban Basics (WIP limits, continuous flow)
- Scaling Agile (SAFe, LeSS, Nexus) – intro level
- Tools included : Jira / Trello setup basics
- Gathering Requirements in Agile
- Just-in-time requirements
- Collaborative discovery
- User Stories & Acceptance Criteria
- INVEST criteria and Definition of Ready / Done
- Story Mapping & Backlog Grooming
- Jira / Confluence Training
- Backlog creation, story linking, boards
- Wireframing & Prototyping
- Tools: Balsamiq / Figma / Draw.io
- Facilitation Techniques
- Agile workshops (Story Mapping, Impact Mapping)
- Agile Planning Levels (Roadmap, Release, Sprint planning)
- Estimation Techniques (Planning Poker, T-Shirt sizing)
- Prioritization Methods (MoSCoW, Kano Model, WSJF)
- Performance Metrics (Velocity, Burnup/Burndown charts , Lead/Cycle Time)
- BA Contribution Metrics (Requirements churn, value tracking)
- How to create and maintain Dashboards in Jira
- Case Study: Analyse sprint reports & suggest improvements
- Stakeholder Management
- Effective Communication
- Facilitation & Conflict Resolution
- Agile Project Simulation End-to-end product backlog creation
- Resume Building for Agile BA
- Mock Interviews & Job Placement
This course is ideal for aspiring Business Analysts, working professionals transitioning to Agile roles, Product Owners, Project Managers, and anyone interested in Agile practices and business analysis.
No technical background is required. The course is designed to help non-technical individuals understand Agile concepts and tools in a practical, easy-to-follow manner.
The duration for Agile Business Analyst training is 2 months (8 weeks), with sessions held 2 times per week (either during week or weekends), including theory, hands-on practice and project work.
Yes, upon successful completion, you’ll receive a Certificate of Completion from Checkmate IT Tech. We also guide you on pursuing global certifications like IIBA-AAC and ICAgile-BA.
Absolutely! The course includes hands-on exercises, case studies, and a capstone project to simulate real Agile environments.
We offer online training classes to promote easy access to all candidates. Recordings are also made available for revision or if you miss a session.
Yes. We provide resume reviews, mock interviews, LinkedIn optimization, and guidance on job portals to help boost your chances in the job market.
You can enroll via our website or contact our support team directly via email or phone. We’ll guide you through the quick and easy registration process.
https://checkmateittech.com/
Email info@checkmateittech.com OR Call Us +1-347-4082054
- Submit Form
Job opportunities in USA and Canada
Prompt Engineer: In charge of creating and refining prompts to communicate with AI models across various industries, guaranteeing that AI systems produce precise and pertinent outcomes.
AI Consultant: Assisting companies in implementing AI solutions by creating efficient workflows and prompts, increasing automation, and boosting business results.
Specialist in Natural Language Processing (NLP): Using prompt engineering to enhance AI’s comprehension of human language to enable more precise and efficient NLP applications.
AI Product Manager: Supervising the incorporation of AI technology and timely optimization into goods and services while ensuring they complement corporate objectives.
Expert in Content Automation: Applying AI technologies to create content and streamline customer support, marketing, and digital media procedures via efficient fast engineering.
As more industries embrace AI-driven solutions, there is a growing need for qualified quick engineers and associated positions in both the USA and Canada. These positions offer attractive pay and opportunities for advancement.
