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Management
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Agile Project Management Essentials
Why participate in the "Agile Project Management Essentials" course? Agile project management methodologies are now widely used not only in the IT sector but also across many trad...
What you'll gain
- ✓ Agile, Waterfall methodologies
- ✓ Scrum and Kanban Frameworks
- ✓ Roadmaps and Story Mapping
- ✓ Metrics and Risk Management
✓ Free consultation · Certificate on completion · Practical learning · Certificate-ready · BDG since 2009
Duration
2 months
Format
Offline
Level
Beginner
Starts
Jul 30, 2026
Certificate
On completion
Schedule
- Thursday · 19:00–21:30
- Saturday · 11:00–13:30
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Access useful books, materials, guides, and learning resources selected to support your development.
Who can you become?
Why participate in the "Agile Project Management Essentials" course?
Agile project management methodologies are now widely used not only in the IT sector but also across many traditional industries. As a result, the global demand for Agile Project Managers continues to grow steadily.If you’ve decided to learn Agile PM and start your journey in the IT field, the "Agile Project Management Essentials" course is designed for you.
Throughout the course, you will learn the core principles of Agile and its key frameworks. The program is fully practice-oriented, allowing you to reinforce your knowledge and apply it in real-life scenarios.
In response to today’s market demands, the curriculum also includes artificial intelligence, along with relevant professional tools and techniques. During the course, you will explore the role of AI in Agile Project Management, learn how to apply essential techniques, understand AI-related risks, and work with performance metrics.
You will also gain a solid foundation in Agile Project Management, study the principles of the Agile Manifesto, and work with frameworks such as Scrum, Kanban, and others, as well as a variety of practical tools. In parallel, you will develop the essential soft skills required for a Project Manager. Hands-on sessions will ensure that your knowledge is reinforced throughout the course.
By the end of the program, you will be prepared to apply for Junior Agile Project Manager positions.
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Who is this course for
-
✓
For beginner
The course does not require any professional knowledge as it is a beginner’s level. You need motivation, hard work, and a desire.
-
✓
Tech sphere professionals
For Tech professionals from other fields who aim to change their career or simply develop skills by learning Project Management.
What you will learn
- ✓Agile, Waterfall methodologies
- ✓Scrum and Kanban Frameworks
- ✓Roadmaps and Story Mapping
- ✓Metrics and Risk Management
- ✓Communication skills
- ✓Team and project management skills
- ✓Role of AI in the Agile Project Management
Program
- Project definitions
- What creates the demand for projects?
- Prioritization and selection of projects
- Who is the Project Manager? Evolution of the modern Project Manager
- Project Management Terminology
- How AI is changing the nature of projects (automation, AI products, data-driven initiatives)
- Project Management Methodologies: Waterfall
- Waterfall application in the Projects: need & possibilities
- Fixed Mindset vs. Growth Mindset
- What is Agile? Understanding the Agile
- When Waterfall still makes sense for AI & data projects (regulation, model validation)
- Agile Manifesto: Understanding the Values
- Agile Deep Dive: 12 Principles of Agile
- Benefits of using Agile
- Challenges and limitations of Agile
- Agile values in AI teams (experimentation, fast feedback, model iteration)
- Agile Development Lifecycle introduction
- Agile Frameworks: Scrum
- Scrum Values: Why they are important.
- Concepts of Iteration Development, Sprints
- Sprinting with AI uncertainty (model tuning, data dependency, spikes)
- Scrum workflow
- Scrum Events/Artifacts and work with them
- Scrum Roles: Who is who in Scrum? Deep dive into Roles
- Scrum challenges and limitations
- Communication with Team/Stakeholders: Do’s and Don’ts
- Intro to XP: practices and pairing with Scrum
- Role shifts in AI teams (PM, Data Scientist, ML Engineer, AI Product Owner)
- Product vs. Project: How to differentiate them
- Product Owner vs. Project Manager
- Product Backlog: Living Document
- User Story: Anatomy of perfect requirement
- Writing Perfect User Stories: INVEST technique
- Prioritization Techniques: The MoSCoW Method, RICE method
- Writing AI-ready user stories (data, model behavior, non-deterministic outcomes)
- What is Lean?
- 5 Lean Principles
- Lean: Limitations & Challenges
- Lean Frameworks: Kanban, Scrumban
- Lean thinking for AI experiments (build–measure–learn with models)
- Kanban: Intro & Four Basic Principles
- Main players in Kanban: Difference with Scrum
- Kanban Board
- Kanban Deep Dive: WIP & Queue Limits
- Bottlenecks: exploring & handling
- Identifying AI bottlenecks (data labeling, training time, infra constraints)
- Requirements preparation & planning in Project Management
- Product Roadmap: Steps to build a buy-in Roadmap
- MVP concepts: What to include
- Epics concepts
- AI roadmaps (PoC → Pilot → Production, model maturity stages)
- User Stories splitting: various techniques (Spidr, CRUD split)
- Story Mapping: Breakdown and validation
- Documentation Management: Confluence, Notion, etc.
- Task Management tools: Jira, Asana, Trello
- Using AI tools for documentation, backlog refinement, and summarization
- Using AI assistants to generate, split, and refine user stories (with human validation)
- Story Points: Concept & Fibonacci sequence
- Story Point vs Hours: pros & cons
- Agile Estimations: Planning Poker & processes
- T-Shirt Estimation, Complexity Buckets & other methods
- Estimating AI work (research spikes, uncertainty buffers)
- Kanban Estimations
- Kanban processes & meetings
- Kanban Metrics: Cycle Time, Lead Time
- Cumulative Flow Diagram
- Metrics that don’t work well for AI, and what to track instead
- Acceptance Criteria introduction
- Definition of Done: Stricting as the project evolves
- Behavior Driven Development
- Project Budgeting: Traditional Method
- Acceptance criteria for AI (accuracy, confidence, explainability)
- Agile Budgeting: Blended Rate & Labor Method
- Role of Project Manager in budget reporting
- Risk Management in Project Management: Waterfall vs Agile
- Introduction to Team Management: Tuckman Ladder
- AI-specific risks (bias, data quality, model drift, legal exposure)
- Definition of bug: Working with defects
- Handling bugs in Scrum, Kanban
- Regression Testing, Unit Testing & Automation testing concepts
- How to control Average Bug age
- Bugs vs model errors, hallucinations, and retraining triggers
- Agile Metrics: Why they are important and how to use them
- Velocity concept: why, how, and when to use it
- Sprint Burndown Chart
- Engineering Metrics: Commits, Active Days and Ratios
- OKR concept
- AI performance metrics (precision, recall, drift indicators) for PMs
Exam includes AI-aware scenarios and decision-making questions for Project Managers
Course details
🗓
Schedule
Thu 7 pm - 9:30 pm,
Sat 11 am - 1:30 pm
💳
Payment
Monthly
🎓
Certificate
On completion
16 lessons
Frequently asked questions
Each course is labelled beginner, intermediate or advanced. If you are unsure, book a free consultation and we will help you choose.
Flexible payment options are available for most programs. Contact us to discuss the right plan for you.
Certificates
Certificates you can receive
Depending on the course format and results, students can receive one of BDG's certificate types.
- ✓ Verified BDG certificate
- ✓ QR / signature-ready format
- ✓ Armenian & English certificate design
Co-branded
Participation
For students who actively participate in the course learning process.
For active participationCompletion
For students who complete the course requirements and finish the program.
For successful completionExcellence
For students who complete the course with outstanding results and strong performance.
With distinctionHR Drone
A co-branded certificate for selected HR and partner-certified programs.
Co-brandedManagement
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2 months · Starts — Jul 30, 2026
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