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Forecasting Models Course (4 Courses, 14+ Projects)
This Forecasting Models Training includes 4 courses , 14 Projects with 54+ hours of video tutorials and Lifetime Access.
In this course, you will be introduced to many statistical tools and essentials in Microsoft excel and using machine learning, Python, Data Science and R programming you will be designing and understanding the better concepts for forecasting models. In this course, you will also be provided with a few hands-on projects and examples to implement and understand the concepts learned throughout the course.
Statistical Tools in Microsoft Excel
Machine Learning - Statistics Essentials
Statistics for Data Science using Python
Statistics Essentials for Analytics
Project on ML - Predicting Prices
* One Time Payment & Get Lifetime Access
What you get in this Forecasting Models Course?
Mobile App Access
About Forecasting Models Course
|Course||No. of Hours|
|Statistical Tools in Microsoft Excel||1h 14m|
|Mathematical and Statistics Foundations for Machine Learning||8h 01m|
|Statistics Essentials with Python||3h 26m|
|Statistics Essentials for Analytics - Beginners||1h 7m|
|Project on ML - Predicting Prices using Regression||2h 21m|
|Project on R - Forecasting using R||4h 47m|
|R Practical - Telecom Customer Churn Prediction||1h 32m|
|Project on Term Deposit Prediction using Logistic Regression CART Algorithm||1h 42m|
|Project - House Price Prediction using Linear Regression||3h 24m|
|R Practical - Employee Attrition Prediction using Random Forest Technique and R||2h 2m|
|Project on R - Card Purchase Prediction||2h 31m|
|R Practical - Predictive Model for Term Deposit Investment||3h 12m|
|Decision Tree Case Study Using R- Bank Loan Default Prediction||1h 51m|
|Project on ML - Churn Prediction Model using R Studio||1h 25m|
|Time Series Analysis in Python - Sales Forecasting||2h 18m|
|Machine Learning Python Case Study - Predictive Modeling||7h 1m|
|Python Data Science Case Study - Predicting Survival of Titanic Passengers||1h 51m|
|Machine Learning Python Case Study - Diabetes Prediction||1h 05m|
|Course Name||Online Forecasting Models Course|
|Deal||You get access to all 4 courses, 14 Projects bundle. You do not need to purchase each course separately.|
|Hours||54+ Video Hours|
|Core Coverage||The main aim of this course is to provide a wide understanding of forecasting models using Excel and programming languages such as R, Python.|
|Course Validity||Lifetime Access|
|Eligibility||Anyone serious about learning data forecasting|
|Pre-Requisites||Basic knowledge about Excel and programming|
|What do you get?||Certificate of Completion for each of the 4 courses, 14 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 skills|
|Type of Training||Video Course – Self Paced Learning|
|System Requirement||1 GB RAM or higher|
|Other Requirement||Speaker / Headphone|
Forecasting Models Course Curriculum
This course focuses on the study of different forecasting models which helps in predicting the outcomes more easily in the field of business and marketing. It helps trainees deal with today’s time of uncertainty along with increased competition and volatile customer loyalty. After the completion of the course the trainee will be able to forecast data and adapt to different changes.
The fundamental objective of this program is to guide the individuals who are ready to learn the forecasting models from the beginning. This training program is completely based on the different forecasting methods like statistical tools in Microsoft Excel, machine learning – statistics essentials, statistics for data science using python, statistics essentials for analytics, and many more other modules.
This training program includes eight main modules of training which are outlined in such a way that all the necessary information are highlighted:
Statistical Tools in Microsoft Excel is the first module of the training program where you will learn about how different statistical tools of Ms. Excel are used in forecasting data. It will be explained through a video tutorial of 1 hour long in which brief detailing of these tools will be done.
Machine Learning – Statistics Essentials will be next about how to use descriptive statistical methods to transform raw observations into information that you can understand and share through a video tutorial of almost 8 hours.
Statistics for Data Science using Python is the third module about how python can be used in data science for statistics. It will be explained briefly in the session.
Statistics Essentials for Analytics is next to where the importance of the self-made data is designed in such a manner that it is easy for a future to get a solid foundation on the concepts. The complete mechanism is explained in detail in terms of Statistical data.
Employee Attrition Prediction is in which under stable circumstances, wherein a set pattern can be assumed from certain parameters for influencing the employee and the organization at all times. Some of these parameters could be probable such as retirement age or unforeseeable such as company performance, external funding, management shakeup, etc.
Decision Tree Case Study Using R is next in which the versatile Machine Learning algorithm of the decision tree can perform both classification and regression tasks. This is known to be a very powerful algorithm, capable of fitting complex datasets. It will help the trainee to fit complex problems on the datasheet easily.
Project on ML – Predicting Prices is the first project on how machine learning can help predict prices using various factors. The detailed information about the projects will be explained by a video tutorial of almost two hours long.
Project on R – Forecasting using R is the next project where forecasting of data will be prepared using R programming so that data can be visualized; it includes patterns, unusual observations, and changes over time are recorded altogether.
Project on R – Telecom Customer Churn will be the next project where you need to predict employee turnover which can be predicted by customer churn using the telecom dataset. Different methods of analysis tools can be used.
Project on R – Predictive Model is the next in which using different concepts of R programming to build a predictive model that can be used to make the statistical and math computation easy and better than machine learning. Details will be explained using the video tutorials.
Project on ML – Churn Prediction Model is next in which we have to predict the percentage of customers that discontinue using a company’s products or services during a particular period using machine learning. The detailed information about the projects will be explained by a video tutorial of almost one hour long.
Project on Python Data Science will be the last project in this training program in which you need to make a project on data science using python programming as it is an open-source, understandable, high-level language and which provides a great approach for object-oriented programming so how it can be used.
Forecasting Models Course- Certificate of Completion
What is Forecasting Models?
Forecasting in general means to display, where this exactly is to display or predict future trends using previous or historical data as inputs to obtain an efficient and effective estimation from the predictive data. Forecasting models have different methods for different situations and evaluation procedures are also conducted. Forecasting evaluation includes a procedure to be carried out in step by step that starts with testing of assumptions, testing data and methods, replicating outputs, and accessing outputs. There are three different types of forecasting which basic types of forecasting are: qualitative techniques, time series analysis and projection, and casual models.
Forecasting is very important and effective technique in various sectors like business, finance, banking, weather, etc which is important in conducting the production planning and management which will help in deciding what to produce and with what available resources to produce, hence this technique is considered as an independent component in the field of business, financial, etc which aids in taking correct decision by the management in the organization or companies.
What skills will you learn in this Course?
In this Forecasting Models Training, as there are a lot of hands-on projects there are many different concepts and skills that are taught during this course. Let us see below:
- In this course, you will learn about statistical tools that are used in Microsoft excel for developing and analyzing the forecasting models.
- In this course, you will master the skills related to machine learning such as decision tree, random forest, etc to implement these algorithms that are used in predicting the forecasting model.
- In this course, you will be even learning skills related to Data Science in which you will learn about techniques and methods in this subject that are used for predicting the efficient data that can be used in predicting future trends.
- In this course, you will also learn skills related to Python. This includes pandas topics which are used for implementing data science and machine learning algorithms.
- In this course, you will also learn about R programming which is a programming language that is used to implement the concepts and plot the graphs and also perform visualizations that can help in predicting the crucial data.
- In this course, you will also learn skills related to banking sectors which will help in predicting the credit card fraud detection analysis.
- In this course, you will learn topics related to time series analysis for which forecasting models are created to analyze the data and predict future trends.
- This course does not require any prior knowledge for undergoing this Forecasting Models Training. There is no need for the advanced concept of any programming language.
- In this course, there is a need for basic knowledge of R and Python programming. This is better to understand the concepts very quickly and easily.
- There is no need for deep knowledge of machine learning and data science, but few basic algorithms and concepts are necessary to know as it will be easy to understand and implement.
- This course can be taken who are interested and want to explore more knowledge in data and analytics.
- This course is helpful for analysts who can easily analyze any huge data and apply the proper algorithm to predict the future trend in the obtained data.
- Technical managers or software engineers or IT operators can also undergo this Forecasting Models Training which will help them upgrade their skills related to time series and forecasting models.
- Students or professionals can also undergo this training who is interested in developing their career or promoting themselves in the field of data science.
FAQ’s- General Questions
What if I any queries or doubts regarding the registration for this course?
The registration for the course is very simple. It is just that you need to sign up with all your credentials and pay the fees. After this still, if there is any query then you can write to us to firstname.lastname@example.org.
Who are the instructors for this course?
As this is an online course, the instructors will be teaching you online and most of the instructors are with industrial experience in these topics as well as of online tutoring. They all provide practical knowledge of these concepts so that it will be helpful in the future for those who are interested in working in this sector.
What are the job roles eligible after this Forecasting Models Training?
After undergoing this course, you are open to wide opportunities for jobs in the data science sector. The job roles that are eligible after this course are data analysts, technical managers, data engineers, software engineers, etc.
- This course will help students or professionals who are willing to endorse their skills or interests in learning data and analytics.
- This course is helpful for the data scientists to upgrade their skills related to data science and can implement different projects that are helpful in company projects to understand and develop solutions to the problems.
- This training is also useful for the employees or the owners so that they can handle their organization and companies by predicting the future trend and can also help in analyzing the business data.