Adapting Agile Frameworks (Scrum, SAFe) for AI and Machine Learning Projects Training by Tonex
The Adapting Agile Frameworks Workshop by Tonex is designed to help teams effectively use Agile methodologies like Scrum and SAFe in AI and machine learning projects. Participants will learn how to align Agile principles with the unique demands of AI development. This course covers backlog management, iterative delivery, collaboration, and scaling Agile practices for complex AI initiatives. Real-world examples and hands-on exercises provide actionable insights for seamless implementation.
Learning Objectives:
- Understand Agile principles tailored for AI and ML projects.
- Implement Scrum and SAFe in AI development.
- Align iterative approaches with AI workflows.
- Manage AI-specific backlogs and deliverables.
- Enhance collaboration across AI and ML teams.
- Scale Agile frameworks for large AI initiatives.
Audience:
- AI and ML project managers.
- Scrum Masters and Agile practitioners.
- Data scientists and AI developers.
- Product owners and business analysts.
- IT and software engineering leaders.
- Organizations transitioning to Agile for AI projects.
Course Modules:
Module 1: Agile Principles for AI and ML
- Overview of Agile in software development.
- Unique challenges in AI and ML projects.
- Adapting Agile values for AI initiatives.
- Benefits of iterative development in AI.
- Addressing uncertainty in AI workflows.
- Bridging Agile and data-driven methodologies.
Module 2: Scrum in AI Development
- Fundamentals of Scrum.
- Sprint planning for AI tasks.
- Managing AI-specific product backlogs.
- Defining done in AI deliverables.
- Role of Scrum Master in AI projects.
- Continuous improvement in AI development.
Module 3: Implementing SAFe for AI Projects
- Overview of SAFe for large projects.
- Scaling Agile practices for AI teams.
- Roles and responsibilities in SAFe.
- Managing dependencies across AI workflows.
- Aligning objectives through Agile Release Trains.
- Ensuring value delivery in SAFe for AI.
Module 4: Iterative and Incremental Development
- Handling data preparation and model training.
- Delivering AI solutions in increments.
- Feedback loops for model improvement.
- Testing and validation in iterative cycles.
- Balancing exploration and exploitation.
- Integrating customer feedback into AI solutions.
Module 5: Collaboration in AI and ML Teams
- Encouraging cross-functional teamwork.
- Aligning data science and engineering efforts.
- Communicating effectively with stakeholders.
- Managing expectations for AI deliverables.
- Resolving conflicts in collaborative environments.
- Building a culture of innovation.
Module 6: Scaling Agile for Complex AI Initiatives
- Strategies for scaling Agile in AI projects.
- Managing multiple AI teams under Agile.
- Leveraging tools for scaled Agile practices.
- Overcoming barriers to Agile scaling.
- Case studies of successful Agile AI implementations.
- Measuring success in scaled Agile AI projects.
Streamline your AI and machine learning projects with Agile frameworks tailored for success. Join Tonex’s Adapting Agile Frameworks Workshop to revolutionize your approach to AI development. Enroll today and lead your teams to excellence!