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PREDICTIVE MODELING Course Bundle - 17 Courses in 1
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.
* One Time Payment & Get Lifetime Access
What you get in this PREDICTIVE MODELING Course Bundle - 17 Courses in 1?
Course Completion Certificates
Mobile App Access
About PREDICTIVE MODELING Course Bundle
|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|
PREDICTIVE MODELING Course Bundle Curriculum
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.
MODULE 1: Predictive Modeling Essentials Training
Courses No. of Hours Certificates Details Predictive Analytics & Modeling using Minitab 15h 35m ✔ 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 24m ✔ 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 ✔
Certificate of Completion
What is Predictive Modeling?
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.
Industry Growth TrendThe global Advanced Analytics Market size was USD 7.04 billion in 2014 and is projected to reach USD 29.53 billion by 2019, growing at a Compound Annual Growth Rate (CAGR) of 33.2% during the forecast period.
[Source - MarketsandMarkets]
[Source - Indeed]
What tangible skills will I learn from this Predictive Modeling course?
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.
- Skill to analyze data and see a complex pattern: data understanding and pattern extraction is a key skill for predictive modeling and a successful person in this domain should be able to make sense of data in no time. In this course, you will learn how to do that. You will be taught various types of data distribution, data patterns, and data understanding techniques. These skills will help you lifelong in making better and more intuitive decisions in all fields of work.
- Hands-on coding skill: – The predictive modeling course teaches three tools- Minitab, SAS, and SPSS. For that, this predictive modeling course is quite good. For predictive modeling and machine learning course one needs to be comfortable with coding, and hence having a sharp understanding of practical implementation is very important. This course teaches all these skills so that the student is industry ready and can comfortably work in real-life use cases.
- Strong understanding of concepts: – Machine learning concepts such as regression, classification, support vector machines, neural network, ROC curve, and many more concepts are taught which are frequently asked in interviews and which judges a candidate’s understanding of predictive modeling.
- 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.
- 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.
Predictive Modeling Course FAQ’s
In this section, we list out some of the common questions frequently asked by students before enrolling for this course: –
Will this predictive modeling course teach me real-life scenarios of predictive modeling?
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.
Is the field of predictive modeling in demand these days?
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.
Will predictive modeling training help me with practical skills or only theoretical knowledge?
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.
How much time would I need to spend on this in a week?
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.
Will I be able to manage this predictive modeling course with a full-time job?
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.
- Many of our previous students have achieved great career success with this predictive modeling training course and realized their dream of becoming a data analyst and data scientist. Thus, you can very much rely on the career benefits and waste no time in the dilemma. Usually, career benefits come in one of the three terms below: –
- Job change: – You can switch to a more happening job after this course. As soon as you finish the predictive modeling course you can start attending interviews and look out of jobs. People usually become senior data analysts, associate data scientists, data scientists and data visualization experts after taking this predictive modeling course.
- Salary hike: – With a new job, you get better pay. Usually, such skills are paid higher compared to usual software jobs and hence you can expect up to a 30-50% hike in your salary.
- Promotion: – if you show enough enthusiasm, you can get promoted in the current role, get more responsibility and raise the corporate ladder.
- Job satisfaction is a great benefit from this field as happiness ratio is highest currently.
Lee Tze Hui
Completion of predictive modeling and implementation using excel.
SEYNI SOLEY BOUBACAR
Great refresher course