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Learn from Home Offer
TIME SERIES ANALYSIS Course Bundle - 13 Courses in 1
This Time Series Analysis Training includes 14 course with 68+ hours of video tutorials and Lifetime Access. You get to learn about how to use Data Science, Statistics & Machine Learning to build and forecast the models in different organizations or business or financial sectors.
* One Time Payment & Get Lifetime Access
What you get in this TIME SERIES ANALYSIS Course Bundle - 13 Courses in 1?
Course Completion Certificates
Mobile App Access
About TIME SERIES ANALYSIS Course Bundle
|Courses||You get access to all 14 courses, Projects bundle. You do not need to purchase each course separately.|
|Hours||68+ Video Hours|
|Core Coverage||Learn about forecasting data models using sophisticated tools|
|Course Validity||Lifetime Access|
|Eligibility||Anyone serious about learning Time Series Analysis|
|Pre-Requisites||Basic knowledge about programming languages such as R, Python, and tools such as Minitab and SPSS|
|What do you get?||Certificate of Completion for each of the 14 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 Course Bundle Curriculum
MODULE 1: Statistics Essentials Training
Courses No. of Hours Certificates Details Statistical Tools in Microsoft Excel 1h 11m ✔ Mathematical and Statistics Foundations for Machine Learning 8h 24m ✔ Statistics Essentials with Python 3h 23m ✔ Statistics Essentials for Analytics - Beginners 2h 5m ✔
MODULE 2: Forecasting using Time Series
Courses No. of Hours Certificates Details Sales Forecasting using Time Series Analysis in Python 2h 13m ✔ Univariate Time Series Analytics & Modeling with EViews 2h 23m ✔ Time Series Analysis and Forecasting using R 4h 23m ✔
MODULE 3: Predictive Modeling
Courses No. of Hours Certificates Details Predictive Analytics & Modeling using SPSS 13h 17m ✔ Predictive Analytics & Modeling using Minitab 15h 35m ✔ Predictive Analytics & Modeling with SAS 9h 19m ✔ Project on R - Card Purchase Prediction 2h 28m ✔
MODULE 4: Case studies and Practical
Courses No. of Hours Certificates Details Time Series Analysis and Forecasting with MS Excel 3h 5m ✔ Time Series Analysis and Forecasting Modeling with MS Excel 2h 01m ✔ Sales Forecasting using Time Series Analysis in Python 2h 13m ✔
The central idea behind providing this training program on time series is to make people profession with the use of prediction and forecasting techniques that are one of the most demanded skills of the industries. With the help of this training program what would be able to understand the core concepts and different technologies that are required for understanding the time series analysis that is used commonly used for forecasting and prediction of unforeseen events and analysis. The training also helps in bridging the gap between the industry demand and the skills that people hold.
the training program of time series analysis is a bundle of many different tools and technologies that are going to be covered and taught at this training program. The curriculum is developed by keeping in mind different requirements of the industries as well as the individuals who are looking forward to learning something new and demanding too in nature. survival skills that individuals will learn in this training program are statistical tools, Microsoft Excel, machine learning, python, data analysis, forecasting tools and techniques, basics of the R language, and many other skills that are very much demanded in nature. With the knowledge of these skills when would be able to secure a job in the industry as a data analyst, business analyst, predictive analyst, machine learning analyst, consultant, and a pool of other opportunities that are open for the individual once they will complete this training program successfully.
Many skills are going to be covered under this training program. Some of the core skills that one will learn through this program are as follows:
Under the module of statistical tools in Microsoft Excel when will learn about introduction to the statistical tools in Microsoft Excel, references, descriptive statistics, Central tendencies, mean, mode, and median the discovered of the three different parts.
Descriptive statistics that cover dispersion and standard deviation, data analysis tools, data analysis with the use of Central tendencies, correlation and regression, histograms in bar charts using data analysis, moving averages using data analysis, etc.
Under the module of machine learning which emphasis on statistical essentials one will learn about introduction to machine learning with the use of python, introduction to analytics with the use of machine learning, big data in machine learning, imaging trends in machine learning, data mining, supervisor unsupervised learning, basics of statistical sampling, sampling methods machine learning, technical terminology, the error of observation and nonobservation, systematic sampling, cluster sampling, different types of data, qualitative data and visualization, basics of statistics probability, relative frequency probability, joint probability, conditional probability, the concept of independence, basics of statistics random variables, probability distribution, cumulative probability distribution, basics of statistics distribution, geometric distribution, normal distribution, Matrix algebra, transpose of a matrix, properties of the matrix, mathematical expressions and computation, hypothesis testing, types of errors, critical value approach, p-value approach, confidence interval, types of hypothesis testing, normal and no normal distribution, normality test, t-test, a test of independence, regression, covariance, etc.
Under the module of statistics for data science using python, a participant would learn about introduction to data science, calculator mode, calculating dispersion means, basic techniques, testing methods, differences in NumPy packages, exclusive events, statistics for data science, analysis of test statistics, the output of the variables, best fit to the, etc.
Under this module of forecasting, a participant would learn about different forecasting tools and techniques that are used with the use of our language, predictive analysis, predictive analysis using SPSS, etc.
There are many projects involved in this training program that helps to ensure the quality and effectiveness of the learning and skills that a transfer to the participants. Some of the core models later part of this training are as follows:
A project on Eviews that uses univariate time series modeling is a great opportunity for individuals to learn about univariate modeling. Under this one will learn about univariate time series modeling, Correloghlram analysis, estimation of output analysis and interpretation, interpretation of the ARMA model, etc.
A project on forecasting using R language which includes introduction to the business analytics forecasting, introduction to the forecasting, methods of forecasting, steps of forecasting, problems with forecasting, simple forecasting methods, transformation and adjustments, regression and multiple linear regression, time series decomposition, developing different models, etc.
A project on predictive modeling the use of SPSS tool that helps in understanding the introduction to the basics of SPSS tool, generation of output, data loading, etc.
A project on predictive modeling using Minitab that involves the use of reference files, introduction to the project, applications of predictive modeling, etc.
Time Series Course – Certificate of Completion
What is a Time Series?
It can be defined as a series or sequence of data that are indexed in terms of time order or in time intervals which are also known as a discrete sequence of time data that are arranged in equally spaced periods in time. This is a method of analyzing data to extract useful data and its characteristics for predicting future values that are dependent on previous values and choose such a model that helps for better decision making. This method is useful for data that are serially correlated which can be used in business like stock market analysis, website traffic, census analysis, etc.
This is one of the very important methods in a machine learning area and its main objective is to develop a statistical model that provides useful and predictable descriptions from the time series dataset. There are different time series models such as the autoregressive model, integrated model, and moving models, where these three models can be combined to form other models also.
What skills will you learn in this Course?
- In this course, you will learn about new technologies like data science, machine learning, R programming, Python, etc.
- In this Time Series Analysis Training, you will statistical concepts such as statistical tools used in Microsoft Excel, statistical essential for data analysis, statistics are also used for machine learning and data prediction, and plotting the details through the graph.
- This course includes the complete fundamental basics to advanced concepts of statistics and its application in other technical subjects that are use full in analyzing and predicting the data.
- In this course, you will learn machine learning algorithms and related concepts that are required for data analyzing and arranging accordingly or with certain intervals to predict the useful solutions.
- In this course, you will also learn a few concepts of Python such as pandas, NumPy, etc that are used in building predictive models.
- This Time Series Analysis Course does not require any prior knowledge of any programming languages. As in this course, we will cover the concepts from the beginning for statistical tools in Microsoft excel.
- There is a basic understanding of concepts such as quantitative methods; MS Office and paint are needed to know in detail.
- This course requires some basic knowledge on R programming or if not programming at least one should know what R tool is and why and where it is used.
- There is no need for any deep knowledge of machine learning is required for this course, a simple understanding of machine learning concepts.
- There is a need for the basics of Python programming to understand the Python packages or libraries used in analyzing.
- Students or graduates from MBA, BBA stream from HR, marketing, sales and operations, etc can take up this course.
- Working professional from the HR or finance department can also go for this course to upgrade his/ her knowledge.
- Even people who have worked in the area of math or stats can also take up this course where it will be easy for them to understand and can implement quickly.
- Even professionals like financial analysts, market analysts, research analysts, etc can also take up this course to learn the latest technologies and techniques available for analyzing and predicting data.
Do we need to have any prior knowledge for Excel- statistical tools to understand the Microsoft Excel section?
Yes, it is better if we know the basics of concepts such as basic computer knowledge, MS Excel. It is very simple and can learn quickly.
When can I get access to lectures and assignments for this Time Series Analysis Training?
Immediately after registering to this course and after the payments are done you will get the access if not also within 48 hours after registering you will be given access to the portal.
When can I get the course certificate?
As there are different online bundles of training on the portal each training is provided with a different and separate certificate is provided but the certificates are issued only when you complete 70 % of each online training.
- This Time Series Analysis Course can help students or graduates or professionals aim to provide econometric or quantitative or predictive modeling skills which can help them to join the finance sector easily.
- The job roles who can go for later are: as a financial analyst, market managers, data analysts or scientists, data engineers, etc.
- Anyone interested in the Time Series Analysis Course can use the acquired knowledge to identify, predict, aiding to forecast future values, etc