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Time Series Analysis | Time Series Forecasting | Time Series Analysis in R | Ph.D. (Stanford)

Time Series Analysis is a major component of a Data Scientist’s job profile and the average salary of an employee who knows Time Series is 18 lakhs per annum in India and 0k in the United States. So, it becomes a necessity for you to master time series analysis, if you want to get that high-profile data scientist job.

Visit Great Learning Academy, for free access to full courses, projects, data sets, codebooks & live sessions: https://glacad.me/3duVMLE

This full course on Time Series Analysis will be taught by Dr Abhinanda Sarkar. Dr Sarkar is the Academic Director at Great Learning for Data Science and Machine Learning Programs. He is ranked amongst the Top 3 Most Prominent Analytics & Data Science Academicians in India.

He has taught applied mathematics at the Massachusetts Institute of Technology (MIT) as well as been visiting faculty at Stanford and ISI and continues to teach at the Indian Institute of Management (IIM-Bangalore) and the Indian Institute of Science (IISc).

Thus, keeping in mind, the importance of time series analysis, we have come up with this Full-course:

These are the topics covered in this full course:
• Types of statistics – 6:18
• What is Time Series Forecasting? – 21:12
• Components of Time Series – 55:23
• Additive Model and Multiplicative Model in Time Series – 1:16:48
• Measures of Forecast Accuracy – 3:04:55
• Exponential Smoothing – 3:47:50

Time Series Analysis explanation :
https://www.mygreatlearning.com/blog/time-series-analysis-and-forecasting/

Here is a list of our other full course videos:

Probability and Statistics Full Course: https://www.youtube.com/watch?v=z9siRCCElls

Machine Learning with Python: https://www.youtube.com/watch?v=RnFGwxJwx-0&t=287s

Tableau Training for Beginners: https://www.youtube.com/watch?v=6mBtTNggkUk&t=994s

Python for Data Science: https://www.youtube.com/watch?v=edvg4eHi_Mw&t=17669s

Hadoop Full Course: https://www.youtube.com/watch?v=JK2MdJAWEGc

Statistics for Data Science : https://www.youtube.com/watch?v=Vfo5le26IhY&t=6682s
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Practical Time frame Number Breakdown Computing with Stats and Machine Learning

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Time Show Breakdown

Time Series Analysis

A Tool written in Java that performs regression on a dataset sample gotten from https://archive.ics.uci.edu/ml/datasets/Individual+household+electric+power+consumption

The project repo is https://github.com/AdeyemiA/TimeSeriesAnalysis or https://github.com/Sapphirine/TimeSeriesAnalysis

The tool can be adapted for any dataset with only restrictions on the first two columns being the date and time.
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Valuable time Show Breakdown and Predict – Educational course 4 how to TSAF (Example one(1))

To download the TSAF GUI, please click here:
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Please check out www.sphackswithiman.com for more tutorials.

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Hello friends today I’m going to show you how the stock market prediction system works and how machine learning helps you to get the exact estimation of the stock market.

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This Time Series Analysis (Part-1) in R tutorial will help you understand what is time series, why time series, components of time series, when not to use time series, why does a time series have to be stationary, how to make a time series stationary and at the end, you will also see a use case where we will forecast car sales for 5th year using the given data.

Link to Time Series Analysis Part-2: https://www.youtube.com/watch?v=Y5T3ZEMZZKs

You can also go through the slides here: https://goo.gl/RsAEB8

A time series is a sequence of data being recorded at specific time intervals. The past values are analyzed to forecast a future which is time-dependent. Compared to other forecast algorithms, with time series we deal with a single variable which is dependent on time. So, lets deep dive into this video and understand what is time series and how to implement time series using R.

Below topics are explained in this “ Time Series in R Tutorial “ –

1. Why time series?
2. What is time series?
3. Components of a time series
4. When not to use time series?
5. Why does a time series have to be stationary?
6. How to make a time series stationary?
7. Example: Forcast car sales for the 5th year

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Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

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Become an expert in data analytics using the R programming language in this data science certification training course. You’ll master data exploration, data visualization, predictive analytics and descriptive analytics techniques with the R language. With this data science course, you’ll get hands-on practice on R CloudLab by implementing various real-life, industry-based projects in the domains of healthcare, retail, insurance, finance, airlines, music industry, and unemployment.

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2. According to marketsandmarkets.com, the advanced analytics market will be worth .53 Billion by 2019
3. Wired.com points to a report by Glassdoor that the average salary of a data scientist is 8,709
4. Randstad reports that pay hikes in the analytics industry are 50% higher than IT

The Data Science Certification with R has been designed to give you in-depth knowledge of the various data analytics techniques that can be performed using R. The data science course is packed with real-life projects and case studies, and includes R CloudLab for practice.
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2. Mastering advanced statistical concepts: The data science training course also includes various statistical concepts such as linear and logistic regression, cluster analysis and forecasting. You will also learn hypothesis testing.
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What is the difference between Confidence Intervals and Prediction Intervals? And how do you calculate and plot them in your graphs?
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