PREDICTIVE MODELING
Specialization | 17 Course Series
This Online Predictive Modeling Training includes 17 courses with 79+ hours of video tutorials and One year 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.
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What you'll get
- 79+ Hours
- 17 Courses
- Course Completion Certificates
- One year access
- Self-paced Courses
- Technical Support
- Mobile App Access
- Case Studies
- Download Curriculum
Synopsis
- 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: One year 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
Content
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MODULE 1: Predictive Modeling Essentials Training
Courses No. of Hours Certificates Details Predictive Analytics & Modeling using Minitab 15h 32m ✔ Predictive Analytics & Modeling with SAS 9h 19m ✔ Predictive Analytics & Modeling using SPSS 13h 17m ✔ Predictive Modeling Training 1h 6m ✔ -
MODULE 2: Logistic Regression & Predictive Modeling
Courses No. of Hours Certificates Details Predictive Analytics and Modeling with Python 8h 26m ✔ Project on EViews - Regression Modeling 3h 12m ✔ Logistic Regression for Beginners 1h 58m ✔ Logistic Regression & Supervised Machine Learning with R 4h 14m ✔ Predicting Prices using Regression Techniques 2h 18m ✔ Project - Exploratory Data Analysis EDA using ggplot2, R and Linear Regression 2h 07m ✔ Logistic Regression using SAS Stat 4h 26m ✔ -
MODULE 3: Learning from Practicals & Case Studies
Courses No. of Hours Certificates Details Linear Regression & Supervised Learning in Python 2h 28m ✔ Logistic Regression & Supervised Machine Learning in Python 2h 6m ✔ House Price Prediction using Linear Regression in Python 3h 2m ✔ Predicting Credit Default using Logistic Regression in Python 3h 3m ✔ Predictive Analytics Model for Term Deposit Investment with R Studio 3h 2m ✔ Project on R - Card Purchase Prediction 2h 28m ✔
Sample Certificate
Requirements
- There are some pre-requisites for this predictive modeling training course that must be fulfilled otherwise the understanding, of course, could become difficult for some students. Do not worry, the pre-requisite is not very difficult and almost anyone can qualify for that. If not, you can enroll for a bridge course or learn the pre-requisite first and then enroll for this predictive modeling course. These pre-requisites are: –
- Basic statistics understanding such as mean, median, mode, the standard deviation is required. If you have forgotten these simple terms, you can revise your high school statistics class or see a couple of videos on YouTube. These concepts, however, will again be covered in this predictive modeling course, but some previous understanding is good to start with.
- Familiarity with excel is also a good thing. You will not learn excel but you will use excel data in Minitab, SPSS, and SAS too. So, some understanding of MS Excel is needed. If you know VBA tool-pack in excel then it is an added advantage, but not mandatory.
- Because machine learning is based on mathematics and hence it is good that you know the basics of linear algebra such as matrix and determinants, simple calculus like what is differentiation, etc.
- Exposure to one programming language is necessary. If you have studied C or C++ in college that should be sufficient.
Target Audience
- This course is suitable for a wide range of audiences. In this section, we specifically explain this to ensure you know if you are suitable for this predictive modeling training.
- Students from technical or computer science fields are highly welcome, similarly, those from mathematics or statistics background is highly suitable. Most commonly students have a degree in B. Tech / BCA/ B.Sc./ MCA/ M. Sc/ M. Tech or MBA degree.
- Entry-level working professionals from the software field, banking, insurance, share market, information technologies who want to migrate to data analysis are also very suitable and they comprise a major chunk of our class size.
- The predictive modeling course is also suitable for managers and seasoned industry professionals who want to be a consultant or data scientist.
- People from engineering, biotechnology, law, medicine, theoretical computer science, geology, and ocean studies also take this predictive modeling training to do data analysis in their respective fields.
- Our past students have been Pharma and research scientists, Professionals of Equity Research and charted financial accountants, Quantitative and Predictive Modelers and Professionals from these domains.
Course Ratings
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Very explanatory & timely information structured about logistic regression.I didnt had any basic knowledge about logistic regression. this course helped me in getting first hand basic information right from scratch about regression. Best part was structured information.
Pawan Soni
This is good course for those who have zero or little knowledge about 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 question.
Lee Tze Hui
Very well explained . Easy to go through and complex calculations has been explained in a simple way and it is easy to understand. I think for program like this you should provide some excel files with problem and user can follow these exercise in excel with looking at instructor manual/video. That will make it very easy ..Anyways I enjoyed the training.
Bishal Adhikari
The course was totally worth it, right from the basics of regression to getting important research work done on a software named EViews. This course has definitely added something in my gamit of knowledge. Generally courses make you understand the gist with one or two examples but herein we took close to 7 different sectoral examples which definitely ignites the embarking of concepts within you.
Karan Paresh Dharamsey