Big Data on AWS - Training and Certification
Big Data on AWS – Training and Certification 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 AWS by enrolling today. Unlock new career opportunities!
- 10+ Courses
- 30+ Projects
- 400 Hours
Data Engineers: Data engineers are experts in creating and overseeing massive data pipelines who wish to become familiar with AWS services to improve performance and scalability.
Scientists and data analysts: People who want to use AWS platforms for machine learning and predictive analytics, as well as to examine big datasets.
IT & Cloud Architects: Experts looking to use AWS services to create reliable big data architectures for businesses of all sizes.
Developers: Programmers who want to use AWS frameworks and APIs to create and implement big data applications.
Professionals in business intelligence: Those who use AWS big data tools to create dashboards, reports, and insights for decision-making.
Students and IT enthusiasts: People who want to begin a career in cloud computing and big data, with an emphasis on AWS technology.
Big Data Engineer: Creating and overseeing AWS data processing systems while guaranteeing scalability and effectiveness when working with big datasets.
Data Scientist: AWS Machine Learning and analytics services are used by data scientists to extract insights and predictive models from large amounts of data.
Cloud Data Architect: Using AWS technologies like Redshift, Kinesis, and EMR to design big data solutions that satisfy corporate needs.
AWS Solutions Architect: With a focus on big data applications, this professional assists businesses in putting effective and scalable AWS solutions into place.
Business Intelligence Analyst: Using AWS tools to analyze data, generate reports, and give stakeholders useful information.
DevOps Engineer (Big Data Focus): Managing big data deployments and workflows in AWS environments while maintaining operational efficiency is the responsibility of a DevOps Engineer with a focus on big data.
Machine Learning Engineer: Using AWS SageMaker and associated services to implement machine learning models and workflows.
In the USA and Canada, big data specialists with AWS experience are highly sought after in sectors like technology, healthcare, retail, and finance, which provide competitive pay and chances for professional 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
Big Data Engineer: Creating and overseeing AWS data processing systems while guaranteeing scalability and effectiveness when working with big datasets.
Data Scientist: AWS Machine Learning and analytics services are used by data scientists to extract insights and predictive models from large amounts of data.
Cloud Data Architect: Using AWS technologies like Redshift, Kinesis, and EMR to design big data solutions that satisfy corporate needs.
AWS Solutions Architect: With a focus on big data applications, this professional assists businesses in putting effective and scalable AWS solutions into place.
Business Intelligence Analyst: Using AWS tools to analyze data, generate reports, and give stakeholders useful information.
DevOps Engineer (Big Data Focus): Managing big data deployments and workflows in AWS environments while maintaining operational efficiency is the responsibility of a DevOps Engineer with a focus on big data.
Machine Learning Engineer: Using AWS SageMaker and associated services to implement machine learning models and workflows.
In the USA and Canada, big data specialists with AWS experience are highly sought after in sectors like technology, healthcare, retail, and finance, which provide competitive pay and chances for professional advancement.
