Learn from Home Offer

Learn from Home Offer
This Online Predictive Modeling Training includes 17 courses with 79+ hours of video tutorials and Lifetime access. You will also get verifiable certificates (unique certification number and your unique URL) when you complete each of them. This course will help you learn to interpret data for statistical analysis using tools such as SAS, Minitab, SPSS.
Courses | You get access to all 17 courses, Projects bundle. You do not need to purchase each course separately. |
Hours | 79+ Video Hours |
Core Coverage | Predictive modeling using tools such as SAS, Minitab, SPSS. |
Course Validity | Lifetime Access |
Eligibility | Anyone who is serious about learning predictive modeling and wants to make a career in Data/Statistical Analysis |
Pre-Requisites | Basis Statistical concepts |
What do you get? | Certificate of Completion for each of the 17 courses, Projects |
Certification Type | Course Completion Certificates |
Verifiable Certificates? | Yes, you get verifiable certificates for each course with a unique link. These link can be included in your resume/Linkedin profile to showcase your enhanced data analysis skills |
Type of Training | Video Course – Self Paced Learning |
In this section, each module of the Predictive Modeling training is explained briefly.
Here, we provide more details on the predictive modeling course content and explain at a very high-level what concepts will be covered under each course. This should give a fair understanding to the prospective students on what they can expect from this course and how useful will it be for their career goal.
Courses | No. of Hours | Certificates | Details |
---|---|---|---|
Minitab - Predictive Modeling | 15h 43m | ✔ | |
Predictive Modeling with SAS Enterprise Miner | 9h 21m | ✔ | |
SPSS - Predictive Modeling using SPSS | 13h 18m | ✔ | |
Predictive Modeling Training | 1h 6m | ✔ |
Courses | No. of Hours | Certificates | Details |
---|---|---|---|
Machine Learning Python Case Study - Predictive Modeling | 8h 27m | ✔ | |
Project on EViews - Regression Modeling | 3h 12m | ✔ | |
Logistic Regression | 1h 58m | ✔ | |
R Practical - Logistic Regression with R | 4h 14m | ✔ | |
Project on ML - Predicting Prices using Regression | 2h 18m | ✔ | |
Project - Exploratory Data Analysis EDA using ggplot2, R and Linear Regression | 2h 07m | ✔ | |
Logistic Regression using SAS Stat | 4h 28m | ✔ |
Courses | No. of Hours | Certificates | Details |
---|---|---|---|
Linear Regression in Python | 2h 28m | ✔ | |
Python Data Science Case Study - Predicting Survival of Titanic Passengers | 2h 6m | ✔ | |
Project - House Price Prediction using Linear Regression | 3h 12m | ✔ | |
Project - Credit Default using Logistic Regression | 3h 2m | ✔ | |
R Practical - Predictive Model for Term Deposit Investment | 3h 2m | ✔ | |
Project on R - Card Purchase Prediction | 2h 28m | ✔ |
Predictive modeling can be understood as the process of creation, test, and validation of a model. It uses concepts from statistics in predicting the outcomes. Predictive modeling contains a different set of methods like machine learning, statistics, artificial intelligence and so on. These models are made up of several predictors, also called attributes that are likely to impact future results. Predictive modeling is currently the most widely used in computer science, information technology, and information services domain.
This predictive modeling course targets to provide predictive modeling skills as mentioned above to business sectors/domains. Quantitative methods and predictive modeling concepts from this predictive modeling course could be extensively used in many fields to understand the current customer behavior, customer satisfaction, financial market trends, studying effects of medicine in pharma sectors after drugs are developed and administered.
Minitab or SAS and SPSS are among the leading developers in the world towards building statistical analysis software. Across the world, these software’s are used by thousands of companies. These are also used by over 10000 universities and colleges for research and teaching. Some major clients of Minitab, for example, consist of Pfizer, Royal Bank of Scotland, Nestle, Boeing, Toshiba, and DuPont.
Many independent studies conducted by companies like Mckinsey, Gartner, and others have predicted that data science, machine learning, and predictive modeling is going to be the biggest jobs of the 21st century and these professionals are going to be rewarded the best for it.
This course covers many tangible skills that students can count on for jobs and career switch. These skills are explained here to help students understand the value of this predictive modeling course.
In this section, we list out some of the common questions frequently asked by students before enrolling for this course: –
Yes. The predictive modeling course teaches all concepts with several live data from industry and explains many case studies in the lecture. Thus, it is a very practical and actual real-life scenario. For example, it takes stock data and then explains how time series modeling can be done on it.
Predictive modeling is a lot in demand. Almost all IT companies are starting with Machine learning and hence they need trained people. Few years down the line, when all these companies will be established with ML, then they will already have enough ML people and hence the right time to learn this skill is NOW.
The predictive modeling course covers both practical as well as a theoretical skills because both are important. It teaches three software tools Minitab, SPSS and SAS so you can understand that it is very practical as each example is demonstrated in this software.
Typically, you would need to spend 4-5 hours per week, but you can do more or less. As the predictive modeling course is self-paced that should not be a problem.
Time management is a personal thing and if you are determined for it, you can do so. We can say from our experience of teaching hundreds of students that it is possible and doable. As the predictive modeling course is self-paced and comes with a lifetime validity you can certainly manage with your job and other responsibilities.
Great video learning! It is taught nice and clear. At first, a bit slow, but as the course progressed, was the tempo at just the right place with good articulation. The content was good, with some nice examples worked out and examples from real life, but could be made more elaborate. Looking forward to more courses of the same teacher.
Linked
This is a good course for those who have zero or little knowledge of predictive modeling. It covers most of the algorithms to do predictive modeling. It also provides some examples and sample questions for practice. I wish this could provide more study material and more practical questions.
Linked
In this course named “Predictive modeling and implementation using MS excel”, I learned about the statistical calculation using excel. the course is very comprehensive and easy to memorize because of the expertise of the lecturer. with this course, I can avoid many errors when doing statistical calculations like Anova. it also helps me to save time. THANKS, EDUCBA
Linked
The course helped me to get insights on the various hypothesis that are done to do the predictive analysis which helps us to make observations and also make predictions and analyze the behavior of the trend, also working on Minitab was a great experience wherein getting the descriptive analysis is much easier than excel.
Linked
The course was very relevant to my job and will help me in most aspects of my work. The hands-on practical training sessions were very good. The trainer got the learning message across by breaking everything down into simplified sections. Handout material was very good as there is a lot of information in them that will help me in my job.
Linked
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Courses | No. of Hours | |
---|---|---|
Minitab - Predictive Modeling | 15h 43m | |
Predictive Modeling with SAS Enterprise Miner | 9h 21m | |
SPSS - Predictive Modeling using SPSS | 13h 18m | |
Predictive Modeling Training | 1h 6m | |
Machine Learning Python Case Study - Predictive Modeling | 8h 27m | |
Project on EViews - Regression Modeling | 3h 12m | |
Logistic Regression | 1h 58m | |
R Practical - Logistic Regression with R | 4h 14m | |
Project on ML - Predicting Prices using Regression | 2h 18m | |
Project - Exploratory Data Analysis EDA using ggplot2, R and Linear Regression | 2h 07m | |
Logistic Regression using SAS Stat | 4h 28m | |
Linear Regression in Python | 2h 28m | |
Python Data Science Case Study - Predicting Survival of Titanic Passengers | 2h 6m | |
Project - House Price Prediction using Linear Regression | 3h 12m | |
Project - Credit Default using Logistic Regression | 3h 2m | |
R Practical - Predictive Model for Term Deposit Investment | 3h 2m | |
Project on R - Card Purchase Prediction | 2h 28m |
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