Learn from Home Offer

Learn from Home Offer
This Online Predictive Modeling Training includes 2 courses, 15 Projects 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.
Predictive Modeling Training
Project on SAS - Predictive Modeling with SAS Enterprise Miner
Projects on ML - Predictive Modeling with Python
Project - Predictive Modeling using SPSS
Project - Predictive Modeling using Minitab
Course | No. of Hours | |
---|---|---|
Predictive Modeling Training | 1h 6m | |
Predictive Modeling with SAS Enterprise Miner | 9h 21m | |
SPSS - Predictive Modeling using SPSS | 13h 18m | |
Machine Learning Python Case Study - Predictive Modeling | 8h 27m | |
Minitab - Predictive Modeling | 15h 43m | |
Project on EViews - Regression Modeling | 3h 19m | |
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 33m | |
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 |
Course Name | Online Predictive Modeling Course Bundle |
Deal | You get access to all 2 courses, 15 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 2 courses, 15 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 |
Software Required | SPSS, Minitab, SAS, Microsoft Excel for practice |
System Requirement | 1 GB RAM or higher |
Other Requirement | Speaker / Headphone |
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.
Sr. No. | Course Name | Course Duration | Course Description |
1 | Predictive Modelling training | 2 | This predictive modeling course is more than 2 hours long and here students learn about the introduction to predictive modeling, variables and its definition, steps involved in predictive modeling, smoothing methods, regression algorithms, clustering algorithms, neural network and support vector machines. Each concept is covered with enough examples and practice exercises. Basics of statistics and data visualization are also covered. Special emphasis is given to data preprocessing, data preparation, model evaluation, and deployment. Data distribution, data plotting, and charts, correlation vs causation, model interpretation, model improvement, etc. are also covered in this module. |
2 | SAS – Predictive Modeling with SAS Enterprise Miner | 9 | This predictive modeling course is 9.5 hours long and is quite extensive. It covers topics such as PM SAS EM Introduction, PM SAS EM variable selection, SAS PM EM combination, SAS PM EM neural network, and SAS PM EM regression. It starts with an introduction to SAS and then gradually move towards topics such as selecting SAS tables, creating input data nodes, decision tree in SAS, creating score model, ROC chart, Neural network training, regression -table effect to name a few. This module covers everything that SAS includes for predictive modeling. |
3 | Predictive Modeling using Minitab | 16 | Minitab is another important tool for predictive modeling. This predictive modeling course on Minitab is about 16 hours long and covers topics such as Minitab and its application in predictive modeling, ANOVA using Minitab, Correlation techniques, regression modeling, predictive modeling using MS Excel. Under each of these heading, various small topics are covered. These are descriptive statistics, nonlinear regression, Anova, control charts, etc. This module contains various case studies from finance and other domains to explain important concepts. |
4 | Predictive Modeling using SPSS | 13 | This module is more than 13 hours long and focuses on the implementation of predictive modeling using SPSS. SPSS is developed by IBM and is another widely used tool for predictive modeling. This predictive modeling course covers topics such as importing data to SPSS, correlation techniques, linear regression modeling, multiple linear regression, logistic regression, and multinomial regression. This course describes use cases from financial, pharmaceuticals and manufacturing domains and is very much suitable for students from these domains. |
Total Duration | 79+ Hours |
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 | |
---|---|---|
Predictive Modeling Training | 1h 6m | |
Predictive Modeling with SAS Enterprise Miner | 9h 21m | |
SPSS - Predictive Modeling using SPSS | 13h 18m | |
Machine Learning Python Case Study - Predictive Modeling | 8h 27m | |
Minitab - Predictive Modeling | 15h 43m | |
Project on EViews - Regression Modeling | 3h 19m | |
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 33m | |
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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