Advanced Machine Learning
Advanced Machine Learning Training Online by Checkmate IT Tech offers a transformative journey, elevating your expertise and mastering essential skills. Position yourself for success in the dynamic field of Machine Learning by enrolling today. Unlock new career opportunities!
- 10+ Courses
- 30+ Projects
- 400 Hours
Advanced Machine Learning Training is suitable for the following target audiences:
Data Scientists: Data scientists are experts who want to learn more about sophisticated algorithms and how to use them to solve challenging data problems.
AI/ML Engineers: AI/ML engineers specialize in creating and implementing machine learning systems on a large scale.
Software developers: Developers who want to incorporate cutting-edge machine learning models into systems and applications.
Researchers: Scholars and business professionals are looking for novel approaches to use machine learning to create ground-breaking solutions.
Students and Enthusiasts: Business analysts seek to apply cutting-edge machine learning techniques to strategic insights and decision-making.
Students and Enthusiasts: People keen to pursue advanced AI positions or develop a career in machine learning.
Machine Learning Engineer: Create, construct, and refine machine learning models for various applications as a machine learning engineer.
Data Scientist: Data scientists create forecasting models, examine patterns, and offer practical advice.
AI Specialist: Concentrate on implementing AI-driven solutions in industries including retail, healthcare, and finance.
Research Scientist: Engage in cutting-edge AI initiatives in academic or business R&D environments.
Business Intelligence Analyst: Improve data visualization and decision-making by applying machine learning techniques.
Robotics Engineer: Apply machine learning approaches, such as reinforcement learning, to self-governing systems.
Computer Vision Engineer: Use deep learning to create sophisticated image and video analysis tools.
Expert in Natural Language Processing (NLP): Develop models for conversational AI, translation, and text analytics systems.
In the USA and Canada, advanced machine learning abilities are highly sought after in various industries, including healthcare, finance, technology, and e-commerce. These fields offer high incomes and substantial growth potential.
- 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
Machine Learning Engineer: Create, construct, and refine machine learning models for various applications as a machine learning engineer.
Data Scientist: Data scientists create forecasting models, examine patterns, and offer practical advice.
AI Specialist: Concentrate on implementing AI-driven solutions in industries including retail, healthcare, and finance.
Research Scientist: Engage in cutting-edge AI initiatives in academic or business R&D environments.
Business Intelligence Analyst: Improve data visualization and decision-making by applying machine learning techniques.
Robotics Engineer: Apply machine learning approaches, such as reinforcement learning, to self-governing systems.
Computer Vision Engineer: Use deep learning to create sophisticated image and video analysis tools.
Expert in Natural Language Processing (NLP): Develop models for conversational AI, translation, and text analytics systems.
In the USA and Canada, advanced machine learning abilities are highly sought after in various industries, including healthcare, finance, technology, and e-commerce. These fields offer high incomes and substantial growth potential.
