Intermediate Machine Learning
Intermediate Machine Learning Course Online by Checkmate IT Tech offer 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
Intermediate Machine Learning Training is suitable for the following target audiences:
Data Scientists and Analysts: Data scientists and analysts are experts who wish to learn more about machine learning algorithms and use cutting-edge methods to solve practical issues.
Software developers: Those who want to improve their programming skills by adding machine learning features to apps.
AI Enthusiasts: AI enthusiasts have a foundational understanding of machine learning and a strong desire to learn more to address increasingly challenging AI problems.
Students and Academicians: People who are interested in working in the fields of machine learning, data science, or artificial intelligence.
Business analysts: These analysts want to use machine learning to make data-driven decisions, plan strategically, and do predictive modeling.
Machine Learning Engineer: Create and implement machine learning models to enhance goods and services in the banking, healthcare, and technology sectors.
Data Scientist: Examine huge datasets using machine learning to find trends and offer useful insights.
AI Research Scientist: Develop novel solutions by working on state-of-the-art machine learning and artificial intelligence research.
Business Intelligence Developer: To improve reporting and analytics capabilities, including machine learning models into BI platforms.
Software Engineer emphasizing ML/AI: Create software programs that use machine learning techniques to provide more intelligent solutions.
Product Manager (AI/ML): Ensure AI-powered solutions are developed and implemented under company objectives.
AI Consultant: Offer companies guidance on incorporating machine learning solutions to address operational issues and spur expansion.
With high-paying employment prospects and room for advancement in the USA and Canada, machine learning talents are highly sought in various industries, including technology, healthcare, finance, e-commerce, and more.
- 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 and implement machine learning models to enhance goods and services in the banking, healthcare, and technology sectors.
Data Scientist: Examine huge datasets using machine learning to find trends and offer useful insights.
AI Research Scientist: Develop novel solutions by working on state-of-the-art machine learning and artificial intelligence research.
Business Intelligence Developer: To improve reporting and analytics capabilities, including machine learning models into BI platforms.
Software Engineer emphasizing ML/AI: Create software programs that use machine learning techniques to provide more intelligent solutions.
Product Manager (AI/ML): Ensure AI-powered solutions are developed and implemented under company objectives.
AI Consultant: Offer companies guidance on incorporating machine learning solutions to address operational issues and spur expansion.
With high-paying employment prospects and room for advancement in the USA and Canada, machine learning talents are highly sought in various industries, including technology, healthcare, finance, e-commerce, and more.
