Course HighlightsCOURSE
Predictive Modeling Fundamentals I

Predictive Modeling Fundamentals I

Discover the world of predictive modeling and learn how business users, data scientists, and developers extract insightful predictions from data. Explore the capabilities of IBM SPSS Modeler.

Master the basics of this critical skill and open up new opportunities in the fast-expanding field of big data analytics.

Predictive Modeling Fundamentals I Highlights

  Course duration

Duration

  • 1 week ,
    5 hrs/week
  Course Fee

Fee

US$ 99 - US$ 199

Course duration

Duration

  • 1 week ,
    5 hrs/week
Course Fee

Fee

US$ 99 - US$ 199

The data industry touches all sectors. Big data itself is a mix of structured, semi-structured, and unstructured data that is gathered from many sources. It is used in machine learning programs, predictive analytics, and other advanced insight applications. And it offers insightful possibilities that range from relatively simple behavioral information to highly complex and nuanced data science.

Predictive analytics brings together advanced analytics capabilities that span across ad-hoc statistical analysis, predictive modeling, data mining, text analytics, entity analytics, optimization, real-time scoring, and machine learning.

During this course, you will learn how to describe predictive modeling and you will discover how and why it is used. You will develop a good understanding of the CRISP-DM methodology and the IBM SPSS Modeler Workbench. You will also explore common modeling techniques, and learn how to prepare, model, and evaluate data using IBM SPSS Modeler.

For learners keen to excel in the world of big data, developing skills in analysing data is a critical first step. This course will provide you with the fundamentals you need in predictive modeling to move onto more advanced learning in the field.

This course comprises five purposely designed modules that take you on a carefully defined learning journey.

It is a self-paced course, which means it is not run to a fixed schedule with regard to completing modules or submitting assignments. To give you an idea of how long the course takes, it is anticipated that with 5 hours of study you will be able to complete it. However, as long as the course is completed by the end of your enrolment, you can work at your own pace. And don’t worry, you’re not alone! You will be encouraged to stay connected with your learning community and mentors through the course discussion space.

The materials for each module are accessible from the start of the course and will remain available for the duration of your enrolment. Methods of learning and assessment will include videos, reading material, and online exams questions.

As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues. Depending on the payment plan you have chosen, you may also have access to live classes and webinars, which are an excellent opportunity to discuss problems with your mentor and ask questions. Mentoring services may vary package wise.

Once you have successfully completed the course, you will earn your IBM Certificate.

After completing this course, you will have:

  • Ability to describe what predictive modelling is and why it is used.
  • Understanding of CRISP-DM methodology and the IBM SPSS Modeler Workbench.
  • Understanding of common modelling techniques.
  • Ability to use IBM SPSS Modeler, e.g. to solve a Kaggle competition.
  • Understanding of how to prepare, model and evaluate data using IBM SPSS Modeller.
  • Individuals keen to combine business with predictive analytics.
  • Aspiring business users, data scientists, and developers keen to use SPSS modeller and SPSS.
  • Individuals seeking to expand their knowlege in big data analytics.
  • A basic knowledge of business statistics is recommended but not required.
Predictive Modeling Fundamentals I

FAQs

Predictive modelling uses statistics to predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. 

Predictive analytics brings together advanced analytics capabilities spanning ad-hoc statistical analysis, predictive modeling, data mining, text analytics, entity analytics, optimization, real-time scoring, machine learning and more. 

Predictive Modelling Fundamentals I is provided 100% online. You will therefore need access to the internet to be able to use the course materials. When you enroll for this course, you be able to access the course materials from the course link in your dashboard immediately. Please note, this course has been designed to be taken with Predictive Modelling Fundamentals II, we therefore recommend that you complete this course and then enroll for Predictive Modelling Fundamentals II when you are ready. This will ensure you have covered the required topics for this subject. 

Yes. Predictive Modeling Fundamentals I is 100% online. You will not be required to attend any classes in person. To enable this, however, you do need to have appropriate access to the internet for the live sessions, plus the required technology to be able to use the program materials. The materials for the program are in the form of articles, videos, and knowledge checks.  

This, of course, makes accessing the program very easy wherever you live in the world. However, it can seem lonely to some individuals. The good news is, though, that you will be actively encouraged to connect with others on the program through the discussion space. And you can enjoy assisted mentoring and access to your instructors outside the live sessions too. 

This program has been specifically designed for learners who have never worked in the field of predictive modelling or big data before; you do not need to have background experience at all. It therefore offers an excellent introduction to the subject. However, you will need basic math and statistical knowledge, some basic computers skills, and also some basic programming experience before you start the program. This will help you greatly as you progress.