Python With AI Training
The goal of Python with AI Training is to instruct participants on how to use Python programming for applications related to machine learning (ML) and artificial intelligence (AI). Natural language processing (NLP), computer vision, neural networks, AI methods, and Python basics are all covered in the course. Participants leave the workshop with the skills necessary to create AI models and use Python to deploy data-driven solutions.
- 10+ Courses
- 30+ Projects
- 400 Hours
Python With AI Training is suitable for the following target audiences:
Software developers: People who want to learn more about creating AI and use Python to incorporate AI features into already-existing applications.
Data scientists and analysts: These professionals work with large datasets and wish to improve their capacity to create machine-learning models and carry out sophisticated data analysis.
Researchers and AI Enthusiasts: Students, researchers, and technologists interested in learning more about deep learning, neural networks, and artificial intelligence.
IT Professionals: IT specialists who want to integrate AI tools into IT systems and procedures or who want to move into AI and machine learning roles.
Business analysts: Analysts who wish to leverage AI technology to drive business insights through predictive modeling and data analysis using Python.
AI developer: creating apps with AI capabilities and implementing machine learning models.
Data Scientist: Analyze big datasets and create predictive models with Python and AI to help guide business choices.
Machine Learning Engineer: A machine learning engineer is responsible for developing, testing, and implementing AI systems and machine learning algorithms.
AI Consultant: Offering guidance to companies on how to use AI technologies to enhance operations and offerings.
Research Scientist: Investigating AI and machine learning models while creating novel AI solutions for diverse sectors.
Healthcare, banking, retail, and technology are among the industries in the USA and Canada that seek workers with Python and AI expertise. These positions provide competitive pay, room for advancement, and the chance to work on innovative AI projects that influence technology in the future.
- 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 developer: creating apps with AI capabilities and implementing machine learning models.
Data Scientist: Analyze big datasets and create predictive models with Python and AI to help guide business choices.
Machine Learning Engineer: A machine learning engineer is responsible for developing, testing, and implementing AI systems and machine learning algorithms.
AI Consultant: Offering guidance to companies on how to use AI technologies to enhance operations and offerings.
Research Scientist: Investigating AI and machine learning models while creating novel AI solutions for diverse sectors.
Healthcare, banking, retail, and technology are among the industries in the USA and Canada that seek workers with Python and AI expertise. These positions provide competitive pay, room for advancement, and the chance to work on innovative AI projects that influence technology in the future.
