Statistical thinking for Data Science
Statistical thinking for Data Science 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 Data Science by enrolling today. Unlock new career opportunities!
- 10+ Courses
- 30+ Projects
- 400 Hours
Statistical Thinking for Data Science Training is suitable for the following target audiences:
Aspiring Data Scientists: People looking to advance into data science positions by gaining a foundational understanding of statistics.
Data Analysts: Data analysts want to improve their statistical analysis abilities to gain more profound understanding.
Business Analysts: Business analysts wish to improve their capacity to analyze data to make strategic decisions.
IT and Software Professionals: Engineers and developers that want to integrate statistical techniques into data-driven solutions are considered IT and software professionals.
Students and Academics: People studying economics, computer science, or mathematics and who wish to use statistical reasoning to tackle challenging issues.
Data Scientist: Data scientists create and apply models to forecast patterns and enhance efficiency.
Data Analyst: Analyzing complicated datasets to help guide corporate decisions and strategies is known as data analysis.
Business intelligence analyst: creating reports and visualizations to aid in decision-making.
A machine learning engineer trains models for artificial intelligence applications using statistical techniques.
Quantitative Analyst: A quantitative analyst uses statistical methods to examine market patterns and financial data.
Operations Research Analyst: An operations research analyst uses mathematical and statistical models to optimize systems and procedures.
Professionals with good statistical thinking abilities are in high demand in the US and Canada in sectors like technology, banking, healthcare, retail, and government. These positions provide high compensation, chances for professional growth, and the opportunity to use data to solve practical issues.
- 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
Data Scientist: Data scientists create and apply models to forecast patterns and enhance efficiency.
Data Analyst: Analyzing complicated datasets to help guide corporate decisions and strategies is known as data analysis.
Business intelligence analyst: creating reports and visualizations to aid in decision-making.
A machine learning engineer trains models for artificial intelligence applications using statistical techniques.
Quantitative Analyst: A quantitative analyst uses statistical methods to examine market patterns and financial data.
Operations Research Analyst: An operations research analyst uses mathematical and statistical models to optimize systems and procedures.
Professionals with good statistical thinking abilities are in high demand in the US and Canada in sectors like technology, banking, healthcare, retail, and government. These positions provide high compensation, chances for professional growth, and the opportunity to use data to solve practical issues.
