Target audiences
- Data science team leaders
- Data analysts transitioning to project management
- Analytics project managers
The Data Science Project Management training is designed for professionals who are interested in applying project management methodologies to data science projects. The course covers the fundamental principles of project management in the context of data science, including project planning, risk management, team collaboration, and stakeholder communication. Participants will learn how to apply these principles to data science projects that involve data analysis, machine learning, and data visualization.
Objectives:
- Understand the principles of project management in the context of data science
- Learn how to develop project plans and manage project risks
- Understand the importance of team collaboration and stakeholder communication in data science projects
- Develop an understanding of data analysis, machine learning, and data visualization
- Apply project management principles to data science projects
Conclusion: By the end of the Data Science Project Management training program, participants will have gained essential project management skills necessary for managing data science projects. They will be able to plan, execute, and monitor data science projects effectively and handle any challenges that may arise during project execution. The program will also equip them with technical skills in data analysis, machine learning, and data visualization, enabling them to make data-driven decisions.
Day 1: Introduction to Data Science Project Management
- Overview of project management concepts
- Overview of data science projects
- Understanding project stakeholders and their roles
- Developing a project charter
Day 2: Project Planning
- Developing a project management plan
- Defining project scope and requirements
- Estimating project costs, resources, and timelines
- Creating a project schedule
Day 3: Project Execution and Monitoring
- Managing project risks and issues
- Managing project quality
- Monitoring project progress
- Controlling project changes
Day 4: Data Analysis and Machine Learning
- Understanding data analysis and machine learning concepts
- Data collection and preparation techniques
- Machine learning algorithms and models
- Evaluation of machine learning models
Day 5: Data Visualization and Project Closure
- Data visualization techniques
- Creating reports and dashboards
- Project closure activities
- Lessons learned and continuous improvement
All our courses are provided in business centers located close to the city center.
After your course registration is complete, you will receive the invoice and comprehensive course details, which encompass information about the venue, instructor, classroom location and various logistical aspects.
For more details please contact us here