AI with ChatGPT and other LLMs for Business
With ChatGPT and other large language models (LLMs), artificial intelligence (AI) is the act of processing, comprehending, and producing language similar to that of a human using sophisticated machine-learning techniques. These models make large dataset analysis, customer interaction automation, decision support, content creation, and business process optimization possible. By understanding and producing natural language, AI-driven LLMs help businesses improve data analysis, customer service, marketing tactics, and productivity.
- 10+ Courses
- 30+ Projects
- 400 Hours
AI with ChatGPT and other LLMs for Business Training is suitable for the following target audiences:
Managers and business executives: Perfect for decision-makers looking to use AI and LLMs to boost customer engagement, spur innovation, and automate procedures within their companies.
Professionals in marketing and sales: Ideal for anyone wishing to use ChatGPT and other AI-powered technologies for content production, lead generation, customer outreach, and targeted marketing.
Data Scientists and Analysts: Designed for experts who want to include LLMs into their data analytic processes in order to improve predictions, produce reports, and glean insights from unstructured data.
IT and Software Development Teams: Designed for developers and IT professionals that wish to integrate LLMs into current systems and apply AI solutions for product development, customer support, or business automation.
Consultants and AI Experts: Ideal for AI experts and consultants who want to counsel companies on how to use LLMs to boost productivity, cut costs, and gain a competitive edge.
AI company Strategist: Assisting businesses in using ChatGPT and other AI technologies into their company plans to improve efficiency and decision-making.
AI Product Manager: The role of an AI product manager involves leading the creation and implementation of AI-powered goods or solutions that improve corporate operations.
Machine Learning Engineer: Creating and refining LLMs and other machine learning models to address business-specific problems.
Data Scientist/AI Analyst: Data scientists and AI analysts use AI techniques to analyze data, optimize processes, and produce relevant business insights.
AI Consultant: Offering guidance to companies on the use of AI, with an emphasis on big language models like ChatGPT, to boost marketing, customer support, and operational effectiveness.
Customer Experience Manager (AI Integration): Using chatbots and LLM-driven solutions with AI to improve customer service and engagement.
These positions, which offer excellent pay and substantial prospects for career progression in both the USA and Canada, are in high demand across sectors like government, healthcare, retail, technology, and finance.
- 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
AI company Strategist: Assisting businesses in using ChatGPT and other AI technologies into their company plans to improve efficiency and decision-making.
AI Product Manager: The role of an AI product manager involves leading the creation and implementation of AI-powered goods or solutions that improve corporate operations.
Machine Learning Engineer: Creating and refining LLMs and other machine learning models to address business-specific problems.
Data Scientist/AI Analyst: Data scientists and AI analysts use AI techniques to analyze data, optimize processes, and produce relevant business insights.
AI Consultant: Offering guidance to companies on the use of AI, with an emphasis on big language models like ChatGPT, to boost marketing, customer support, and operational effectiveness.
Customer Experience Manager (AI Integration): Using chatbots and LLM-driven solutions with AI to improve customer service and engagement.
These positions, which offer excellent pay and substantial prospects for career progression in both the USA and Canada, are in high demand across sectors like government, healthcare, retail, technology, and finance.
