What You’ll Learn
  • Fundamentals of HR predictive analytics and its applications
  • Techniques for forecasting HR metrics and trends
  • How to implement linear regression for HR insights
  • How to use logistic regression to predict employee attrition
  • Applying learned techniques to real-world HR scenarios

Requirements

  • A PC/ laptop with good internet connection and MS Excel installed on it

Description

If you're embarking on or advancing within a career that combines HR management with the dynamic field of predictive analytics, acquiring the skill to merge these disciplines is crucial in today's data-centric landscape. HR Predictive Analytics is designed to equip you with the analytical tools and techniques essential for making informed HR decisions and improving employee outcomes. This course demystifies the process of analyzing HR-related data, enabling you to effectively forecast, evaluate, and enhance various HR functions.

In this course, you will:

  • Learn the fundamentals of HR predictive analytics and its applications.

  • Master the art of forecasting HR metrics to predict future trends.

  • Develop skills to implement linear regression and logistic regression for HR insights.

  • Gain proficiency in clustering techniques to segment employee data.

  • Apply your skills through hands-on projects and real-world scenarios to cement your learning.

Why learn HR Predictive Analytics?

Integrating predictive analytics into HR practices offers a competitive edge, enhancing efficiency, and ensuring the success of your HR initiatives. This course will guide you through understanding complex HR data, making predictions about future employee behavior, and implementing strategies to achieve desired outcomes. Whether you are an HR professional, data analyst, business analyst, or student, these skills are invaluable in navigating the complexities of modern HR environments.

Course activities include:

  • Real-world case studies to apply and reinforce your learning.

  • Practical exercises in Excel, focusing on data analysis and modeling techniques.

  • Projects that simulate actual HR challenges, requiring data-driven solutions.

5 Reasons to choose this HR Predictive Analytics course:

  • Comprehensive curriculum blending HR principles with predictive analytics.

  • Hands-on approach with practical examples and case studies.

  • Downloadable resources for practice and application of learned techniques.

  • Guidance from instructors with extensive experience in data analytics and HR 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 broadened my knowledge more on the power use of SQL as an analytical tool. 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 predictive analytics in HR management, enroll in our course today and take the first step towards mastering this essential skill set.

Cheers,

Start-Tech Academy

Who this course is for:

  • HR Professionals: Looking to enhance their skills in predictive analytics to make data-driven decisions and improve HR functions.
  • Data Analysts: Seeking to specialize in HR analytics and apply their data analysis skills to the HR domain.
  • Students and Graduates: Aspiring to build a career in HR analytics and looking for a comprehensive introduction to the field.
Courses

Course Includes:

  • Price: FREE
  • Enrolled: 3950 students
  • Language: English
  • Certificate: Yes

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