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Data Analytics for Project Management


Data Analytics for Project Management

Project analytics are a lifeline for project managers to stay on schedule and on a budget in an environment where projects are growing increasingly complicated.


What you'll learn

  • Basics of project management & data analytics
  • Calculation of Key Performance Indicators (KPIs)
  • Creating effective project dashboards
  • Excel skills for data analysis in project management
  • Learn Forecasting and Predictive models


  • A PC/ laptop with good internet connection and MS Excel installed on it
If you're embarking on or advancing within a career that blends project management with the dynamic field of data analytics, acquiring the skill to merge these disciplines is crucial in today's data-centric landscape. Data Analytics in Project Management is designed to equip you with the analytical tools and techniques essential for making informed decisions and driving project success. This course demystifies the process of analyzing project-related data, enabling you to effectively monitor, control, and predict project outcomes.

In this course, you will:

  • Learn the fundamentals of project management and the role of data analytics.
  • Master the art of calculating and interpreting Key Performance Indicators (KPIs) to gauge project health.
  • Develop skills to create insightful dashboards for real-time project monitoring.
  • Gain proficiency in Excel for managing project data.
  • Apply your skills through hands-on projects and real-world scenarios to cement your learning.
  • Why learn Data Analytics in Project Management?
Integrating data analytics into project management practices offers a competitive edge, enhancing efficiency, and ensuring the success of your projects. This course will guide you through understanding complex data, making predictions about future project performance, and implementing changes to achieve desired results. Whether you are a project manager, data analyst, business analyst, or student, these skills are invaluable in navigating the complexities of modern project environments.

Course activities include:

  • Real-world case studies to apply and reinforce your learning.
  • Practical exercises in Excel, focusing on data analysis and visualization techniques.
  • Projects that simulate actual project management challenges, requiring data-driven solutions.

5 Reasons to choose this Data Analytics in Project Management course:

  • Comprehensive curriculum blending project management principles with data analytics.
  • Hands-on approach with practical examples, case studies, and exercises.
  • Downloadable resources for practice and application of learned techniques.
  • Guidance from instructors with extensive experience in data analytics and project management.
  • A vibrant community of peers for collaboration and support.

What makes us qualified to teach you?

This course is brought to you by Abhishek and Pukhraj, seasoned educators with a decade of experience in teaching data analytics, machine learning, and business analytics. Leveraging tools like Excel, SQL, Python, and Tableau, we've crafted engaging, impactful learning experiences.

We've received thousands of 5-star reviews for our courses, reflecting our commitment to helping students achieve their professional and personal learning goals:

I had an awesome moment taking this course. It broaden my knowledge more on the power use of SQL as an analytical tools. Kudos to the instructor! - Sikiru

Very insightful, learning very nifty tricks and enough detail to make it stick in your mind. - Armand

So, if you're ready to harness the power of data analytics in project management, enroll in our course today and take the first step towards mastering this essential skill set.


Start-Tech Academy

Who this course is for:

  • Professionals seeking to integrate data analytics into project management
  • Students aiming for a career at the intersection of analytics and project management
  • Project managers wanting to enhance decision-making with data insights

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