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Product ID: OC-2026-A2PLF
Data Analytics and Machine Learning for the Technical Project Manager
Learn to manage ML-driven projects by integrating data analysis, applying relevant metrics, and optimizing outcomes. This course equips Technical Project Managers with the skills to lead successful machine learning initiatives in dynamic environments
In partnership with
Overview
Businesses are rapidly adopting Machine Learning, but successful integration requires more than just advanced technology—it demands effective project management. Understanding how ML fits into software and hardware solutions is essential for ensuring meaningful outcomes.
This course covers the fundamentals of managing ML-driven projects, including how a Project Manager interacts with Machine Learning tools, integrates data analysis, and evaluates results for both internal performance and customer impact. You will explore what makes ML outcomes successful, the role of internal and external metrics, and strategies for incorporating ML into project workflows.
Skills you'll gain
Data ScienceMachine LearningData Analytics
What you'll learn
- Evaluate different project management processes for integrating machine learning practices.
- Demonstrate foundational principles of machine learning development within a project framework.
- Analyse various data analytic techniques to assess and measure machine learning outcomes.
- Synthesize key outcomes from an ML project to identify challenges, anticipate roadblocks, and determine essential metrics.
Who Should Attend
Prerequisites
This course is tailored for professionals who lead, support, or contribute to machine learning projects within technical environments. It’s ideal for technical project managers, team leads, and supervisors responsible for integrating ML tools into product development workflows. Developers aiming to understand how ML impacts future tasks and project delivery will also benefit, as will data analysts looking to better build and assess ML models. Additionally, this course is a strong fit for professionals who need to effectively communicate ML objectives and results to both technical teams and business stakeholders.
Learners should have a working knowledge of project management principles—such as Agile, Scrum, or similar methodologies—and a basic understanding of machine learning tools and concepts. Familiarity with large language models (LLMs), analytic workflows, and data processing techniques will help learners follow along more effectively. While coding experience is not required, comfort with data-driven thinking and some exposure to tools like R or Jupyter Notebooks will be advantageous.
Chapters
Explore a structured set of chapters designed to build your skills step by step, with practical examples and hands-on applications.
Meet your instructors
Mark Peters
View my channelFrequently Asked Questions
How much do the courses at Starweaver cost?
We offer flexible payment options to make learning accessible for everyone. With our Pay-As-You-Go plan, you can pay for each course individually. Alternatively, our Subscription-Based plan provides you with unlimited access to all courses for a monthly or yearly fee.
Do you offer any certifications upon completion of a course at Starweaver?
Yes, we do offer a certification upon completion of our course to showcase your newly acquired skills and expertise.
Does Starweaver offer any free courses or trials?
Related Modules
Product ID: OC-2026-A2PLF
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4 hours of video content
Downloadable resources
Certificate of completion
Desktop and Mobile access
Mark Peters