Generative AI Training
Generative AI training aims to teach participants how to create and apply artificial intelligence models that can produce text, images, audio, and even code. This training covers deep learning techniques, natural language processing (NLP), and neural networks such as transformers and GANs (Generative Adversarial Networks) to prepare people to develop AI systems that can generate new data on their own depending on input patterns.
- 10+ Courses
- 30+ Projects
- 400 Hours
Generative AI Training is suitable for the following target audiences:
Data Scientists: Data scientists are experts in the field who wish to broaden their knowledge to incorporate generative AI tools for creative automation and problem-solving.
Researchers and engineers working in artificial intelligence: People who want to learn more about generative models and AI frameworks.
Software developers: Developers who want to improve automation, create cutting-edge user experiences, and integrate generative AI models into applications.
Creative Professionals: Writers, designers, and artists who wish to investigate the relationship between creativity and artificial intelligence, utilizing generative AI to support or enhance their creative outputs.
Business Leaders & Innovators: Entrepreneurs and corporate executives who want to use generative AI to innovate, streamline operations, or develop new AI-powered goods and services are known as business leaders and innovators.
AI/ML Engineer: Create and implement generative AI models, utilizing neural networks, transformers, and other AI technologies to innovate across various industries, including software development, automation, and media.
AI/ML Engineer: As a data scientist with experience in generative AI, I analyze data and create generative models that can forecast trends, provide original content, or streamline procedures.
AI Research Scientist: Push the limits of what AI systems can produce and accomplish by researching and creating new generative AI approaches.
Creative Technologist: Use generative AI to produce digital media, music, literature, and art in partnership with artists, media businesses, or other creative industries.
AI Product Manager: Oversee the creation of AI-powered products, leveraging generative AI to improve automation, innovation, and product features in sectors such as marketing, healthcare, and finance.
In the USA and Canada, there is an increasing need for generative AI specialists in fields including technology, entertainment, finance, and healthcare, which offer competitive pay and quick career 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
AI/ML Engineer: Create and implement generative AI models, utilizing neural networks, transformers, and other AI technologies to innovate across various industries, including software development, automation, and media.
AI/ML Engineer: As a data scientist with experience in generative AI, I analyze data and create generative models that can forecast trends, provide original content, or streamline procedures.
AI Research Scientist: Push the limits of what AI systems can produce and accomplish by researching and creating new generative AI approaches.
Creative Technologist: Use generative AI to produce digital media, music, literature, and art in partnership with artists, media businesses, or other creative industries.
AI Product Manager: Oversee the creation of AI-powered products, leveraging generative AI to improve automation, innovation, and product features in sectors such as marketing, healthcare, and finance.
In the USA and Canada, there is an increasing need for generative AI specialists in fields including technology, entertainment, finance, and healthcare, which offer competitive pay and quick career advancement.
