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TIME SERIES ANALYSIS with R Course Bundle - 19 Courses in 1
This Time Series Analysis and Forecasting with R includes 19 courses with 73+ hours of video tutorials and Lifetime Access. In this course, we are going to learn about one of the most interesting aspects of technology, which is to predict something that can be certain or uncertain. We will be focusing on all sorts of time related data and its analysis using the R programming language with the help of machine learning and predictive analytics.
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What you get in this TIME SERIES ANALYSIS with R Course Bundle - 19 Courses in 1?
73+ Hours
19 Courses
Course Completion Certificates
Lifetime Access
Self-paced Courses
Technical Support
Mobile App Access
Case Studies
About TIME SERIES ANALYSIS with R Course Bundle
| Courses | You get access to all 19 courses, Projects bundle. You do not need to purchase each course separately. |
| Hours | 73+ Video Hours |
| Core Coverage | The main aim of this course is to learn how to use R on real forecasting and time series analysis |
| Course Validity | Lifetime Access |
| Eligibility | Anyone serious about learning Time Series Analysis and Forecasting with R |
| Pre-Requisites | Basic knowledge about R programming, statistics |
| What do you get? | Certificate of Completion for each of the 19 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 skills |
| Type of Training | Video Course – Self Paced Learning |
TIME SERIES ANALYSIS with R Course Bundle Curriculum
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MODULE 1: Statistics Essentials Training
Courses No. of Hours Certificates Details Data Science with R 6h 2m ✔ Business Analytics using R - Hands-on! 16h 21m ✔ Machine Learning with R 20h 25m ✔ -
MODULE 2: Projects based Learning
Courses No. of Hours Certificates Details Predictive Analytics Model for Term Deposit Investment with R Studio 3h 2m ✔ Project on R - Card Purchase Prediction 2h 28m ✔ Random Forest Techniques and R - Employee Attrition Prediction 1h 6m ✔ Predictive Analytics Model for Term Deposit Investment using CART Algorithm 1h 38m ✔ R Practical - Telecom Customer Churn Prediction 1h 27m ✔ Project on ML - Churn Prediction Model using R Studio 1h 22m ✔ Decision Trees - Bank Loan Default Prediction using R 1h 47m ✔ Time Series Analysis and Forecasting using R 4h 23m ✔ -
MODULE 3: Learning from Practicals & Case Studies
Courses No. of Hours Certificates Details Logistic Regression & Supervised Machine Learning with R 4h 14m ✔ Decision Trees Modeling using R 1h 4m ✔ Project - Market Basket Analysis in R 37m ✔ Project - Hypothesis Testing using R 3h 6m ✔ Project - Exploratory Data Analysis EDA using ggplot2, R and Linear Regression 2h 07m ✔ Project on R - HR Attrition and Analytics 2h 4m ✔ Machine Learning Project using Caret in R 1h 58m ✔ Cluster Analysis and Unsupervised Machine Learning - K-Means Clustering using R 43m ✔
Goals
the central Idea behind providing this training program on time series analysis and forecasting with the use of language is to make individuals profession with the use of R language and teach them how to use forecasting and prediction and time series analysis for bridging the gap between the present in the future scenario. Predictive analysis and forecasting are some of the most demanded skills and with the help of this training, individuals would be able to get a job in the industry easily.
Objectives
The training program is a well-defined structure and aims at catering up the requirements of the industry and the individuals who are looking for learning something new and building up their career according to the industry demand. There are a variety of skills that are going to be covered under this training program like predictive analytics, R language, data science, business analytics, and many others gives that are sufficient enough to security job as a data analyst, analyst, data scientist, business analyst, R programmer, machine learning analyst and many other opportunities that will open for individual once they will complete this training program successfully.
Course Highlights
The training program covers a great variety of skills that are going to be taught and covered under this training program. Some of the core skills that are covered are as follows:
Under the module of data science with R, a participant would learn about introduction to data science with the use of R language, understanding data science and its models, different tools, statistical computing, the purpose of R tool, a module on data visualization, creating pie charts, greeting bar charts, creating histograms, methods of using scatter plots, basic data visualization, vector values, regression, understanding linear regression, logistic regression, logistic regression, learning normal distribution curve, binomial distribution, analysis of covariance, time series analysis, least square method, random forest method, etc.
under this module of business analytics using the R language, one will learn about reference, introduction, course curriculum, discriminant analysis, introduction to analytics, the evolution of business analytics, ordinal data, business analytics lifecycle, understanding our language, manipulation in statistics basics, statistics probability and distribution, understanding visualization, etc.
Under this module of machine learning with R language what would learn about introduction to machine language, basic data manipulation in R language, linear regression, square, standard errors, multiple linear regression, generalized linear model and generalized least square, k nearest neighbor model, decision trees classifier and learning decision tree, random forest, k means clustering, naive Bayes classifier, neural networks, time series analysis, market basket analysis, gradient boosting machines, etc.
Project Highlights
There are many real-time and practical projects that a part of this training program that would help individuals to understand the concept in a better way. Some of the core projects that are part of this training program are as follows:
card purchase prediction with the use of R language would help an individual to understand the process behind our language and card purchase prediction.
A project on a predictive model for term deposit investment using R language which includes, problem statement, explanation, model development, model parameters, model improvement, model validation in deployment using R language.
A project on attrition predicting using random forest technique of employees that includes an introduction to the project, deciding the parameters, deployment of the project, validation of the project using R language.
A project on term deposit prediction using logistic regression CART algorithm includes an introduction to term deposit investment predictions, an overview of the project, development of the project.
a project on telecom customer churn prediction using R language includes an introduction to the project, loading of data set, developing model, validating the model.
A project on machine learning based on a prediction model using R studio includes an introduction, types of data, transformation and model, reference files, etc.
a project on forecasting using R that includes different principles of R, forecasting tools and techniques.
Project on logistic regression using R language.
A project on decision tree modeling using, market basket analysis using the R language, hypothesis testing using the R language, HR attrition analytics using the R language, etc.
With the help of these real-time projects and the case studies, one would be available to prepare himself for the real industry scenarios.
Time Series Analysis and Forecasting with R – Certificate of Completion
What is Time Series Analysis and Forecasting with R?
Time series analysis and forecasting can be defined as the approach to predict the certainty based on the sequence of time. It can also be considered as the method that is required to determine the possibilities that could occur based on the data occupied through the last occurrence. R programming language can be used to implement Time Series Analysis and Forecasting in the application level which will eventually help to implement the concepts of data science. As the name suggests, the program has to be written in a manner so that it could be ample power to determine the possibilities based on the past performance of any event or the data gathered from the event that has already occurred. It is very simple to understand and folks with a good understanding of R programming language will be able to write the logic to implement the concepts with ease.
What skills will you learn in this Course?
This course has been equipped with all the essentials that are required to master the skills that one must have to work very effectively with this technology. At the beginning of this course, you will be getting a brief of the concept that falls under the umbrella of Time Series Analysis and Forecasting. In the initial few units, you will get to learn about the basic implementation of this course while later in the course the complexity will increase with the passing time. We have included various projects in this course that could be used to dive deep into the concept of this main topic. In the projects, you will also be learning about various kinds of errors that populate when it comes to implementing the concepts in production. After finishing this course, you will be having all the essential skills that are required to work with the R programming language to implement Time Series Analysis and Forecasting.
Pre-requisites
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- All the topics which are not directly but indirectly concerned with R that endorses the implementation of Time Series Analysis and Forecasting have been considered as prerequisites for this course. There are certain technologies that you should be aware of to facilitate your learning in this course.
- Data science is the first thing that the trainees should be aware of before beginning to take this course. As some of the concepts are based on data science, it will be helpful for the trainees to have a basic understanding of this.
- Machine learning is the next important thing. Folks with a good understanding of ML will find it easy to cover the units and projects that are solely based on ML.
If you are having a good understanding of these technologies, it will be very easy for you to complete this course while if you are new to these concepts, don’t worry, we got them covered in this course.
Target Audience
- Anyone willing to master the approach that is required to learn the implementation of Time Series Analysis and Forecasting can be the best target audience for this course.
- All the professionals, students, and trainers can be the best target audience for this course.
- The developers who are working in some other programming language and want to learn about the complex aspect of R programming language can be the best target audience for this course. They will be learning how to implement Time Series Analysis and Forecasting from scratch in R.
- The students who are interested in diving deep into R can also be the best target audience for this course and can also be the best target audience for this course. They will be learning everything from a beginner’s point of view.
- The educators who are training folks in R programming language can also be the best target audience for this course. After completing this course, they will be able to implement the concepts from scratch.
FAQ’s- General Questions
How long it may take to complete this course?
One could complete this course within one or two weeks but to master the concepts, one will need to practice things over and over, and based on their familiarity with the concepts, it may depend on how long they need to practice things. One who is having a good understanding of R programming language may take around one month to practice the concepts while the folks who are fresh to R will need to practice it for around two months. After they complete practicing things for longer, they will be able to work very proficiently with this technology.
Why should I take this course?
Folks who are willing to learn Time Series Analysis and Forecasting in R programming language can take this course to grab all the aspects that one needs to implement the concepts. All the concepts detailed in this course have been explained well using simple examples that are required to make it easy for the trainees to understand things. In addition to these, the language that is used to detail the concepts are very simple which makes it easy for the trainees to get a good understanding of all the concepts detailed in this training. The trainees will find it very easy to complete this course and they will also be able to implement everything from scratch right after they are done with this course and practicing the same for some time.
Sample Preview
Career Benefits
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- R programming language has been used very extensively everywhere to implement the concepts of data science and others as well. Time Series Analysis and Forecasting is one of the most important concepts that help to implement procedures for prediction.
The organizations all across the world keep on looking for a professional who is an R expert and has a good understanding of Time Series Analysis and Forecasting.
In the current job market, the count of opportunities for R programming language is pretty high and it is supposed to keep on increasing with the growth in demand of complex tools to ensure the smooth conduct of business operations.
If one is willing to learn the implementation of Time Series Analysis and Forecasting, they can opt for this course and give an amazing turn to their career. It is very easy to take this course and you can begin the training right within a few clicks.
Reviews
Completion of predictive modeling and implementation using excel.
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
SEYNI SOLEY BOUBACAR
Predictive Modeling
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.
Lee Tze Hui
Amazing course
There are too many good points to list! 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.
