- Course introduction
- Introduction to forecasting and time series analysis
- Pandas time series notebook - part 1
- Pandas time series notebook - part 2
- Pandas time series notebook - part 3
- Pandas time series notebook - part 4
- Time series decomposition
- Decomposition models
- Decomposition notebook - part 1
- Decomposition notebook - part 2
Intermediate
Online
4 Weeks
Free
Quick facts
particular | details | |
---|---|---|
Medium of instructions
English
|
Mode of learning
Self study
|
Mode of Delivery
Video and Text Based
|
Course overview
By taking up the Specialized Models: Time Series and Survival Analysis online course the students will be working on the ways to identify the modelling challenges that are common within the domain of time series data. The course will further be helping to understand the process of how trends are gauged and accessed in a time series of data. In the Specialized Models: Time Series and Survival Analysis certification syllabus the students will be covering chapters on- Identifying Nonstationarity, Common Transformations, Smoothing Moving Averages, Time Series Smoothing, Deep Learning Notebook, Survival Analysis and Censoring and others. The online course on Specialized Models: Time Series and Survival Analysis by Coursera will be elaborating on the domains of “time-series data” and will be working on its applications.
The highlights
- 100% online programme
- 11 hours total course duration
- Programme by Coursera
- Shareable certificate
- Course offered by IBM
- Subtitles in English
- Intermediate level course
- Deadlines flexible
- Course level intermediate
Program offerings
- Online course
- Quizzes
- Assignments
- Practice sets
- Video lectures
- Subtitles
Course and certificate fees
Type of course
- The Introduction to Git and GitHub fee for enrollment is free for 7 days only.
- They need to pay Rs. 2,378 to access the course ahead.
Fee Details
Particulars | Amount |
Enrollment fee | Free |
Certification fees | ₹2,378 |
certificate availability
certificate providing authority
certificate fees
Eligibility criteria
Education
For applying in the Specialized Models: Time Series and Survival Analysis programme the students to need to have a fair understanding of Python, Calculus, Exploratory data analysis, Linear Algebra, Probability, Supervised machine learning, Unsupervised machine learning and Statistics.
Certification Qualification Details
For receiving the certificate the students need to complete the Specialized Models: Time Series and Survival Analysis programme in the stipulated time frame.
What you will learn
After completing the Specialized Models: Time Series and Survival Analysis online course the students will learn about-
- Students will get their skills enhanced in the genre of deep learning.
- The chapter on survival analysis forecasts will be covered in details.
- Applicants will be working on the mechanisms of “stationary notebook”.
- In the Specialized Models: Time Series and Survival Analysis certification syllabus the students will cover the chapter of “Time Series Smoothing”.
- The details and working mechanisms of machine learning will be covered.
Who it is for
The Specialized Models: Time Series and Survival Analysis programme is for the following students-
Admission details
Filling the form
For getting enrolled in the Specialized Models: Time Series and Survival Analysis online course the students need to follow the listed steps-
Step 1: The URL mentioned below needs to be visited by the interested students- https://www.coursera.org/learn/time-series-survival-analysis
Step2: The candidates who are interested in applying for the course have to click on the “enroll” button.
Step 3: Students have to select the course given.
The syllabus
Week 1: Introduction to time series analysis
Videos
Readings
- Time series demo (activity)
- Time series decomposition demo (activity)
- Summary/review
Practice exercises
- Check for Understanding
- Check for Understanding
- End of Module Quiz
Week 2: Stationarity and time series smoothing
Videos
- Stationarity and autocorrelation
- Stationarity notebook - part 1
- Stationarity notebook - part 2
- Stationarity notebook - part 3
- Nonstationarity examples
- Identifying nonstationarity
- Common transformations
- Time series smoothing
- Smoothing moving averages
- Smoothing exponential intro
- Advanced smoothing
- Smoothing notebook - part 1
- Smoothing notebook - part 2
Readings
- Stationarity demo (activity)
- Time series smoothing demo (activity)
- Summary/review
Practice exercises
- Check for Understanding
- Check for Understanding
- End of Module Quiz
Week 3: ARMA and ARIMA models
Videos
- Autoregressive models and moving average models
- Useful Plots
- ARMA models notebook -part 1
- ARMA models notebook - part 2
- ARIMA and SARIMA Models1
- SARIMA prophet notebook - part 1
- SARIMA prophet notebook - part 2
- SARIMA prophet notebook - part 3
- SARIMA prophet notebook - part 4
- ARMA models demo (activity)
- SARIMA prophet demo (activity)
- Summary/review
Readings
- ARMA models demo (activity)
- SARIMA prophet demo (activity)
- Summary/review
Practice exercises
- Check for Understanding
- Check for Understanding
- End of Module Quiz
Week 4: Deep Learning and survival analysis forecasts
Videos
- Deep learning - part 1
- Deep learning - part 2
- Deep learning - part 3
- Deep learning notebook - part 1
- Deep learning notebook - part 2
- Survival analysis and censoring - part 1
- Survival analysis and censoring - part 2
- Survival analysis notebook
- Deep learning for Forecasting demo (activity)
- Survival analysis demo (activity)
- Summary/review
Readings
- Deep learning for forecasting demo (activity)
- Survival analysis demo (activity)
- Summary/review
Practice exercises
- Check for Understanding
- Check for Understanding
- End of Module Quiz
Scholarship Details
Note: Financial aid is available but the amount has not been specified.
How it helps
The Specialized Models: Time Series and Survival Analysis certification benefits the candidates by allowing them a platform to develop more skills in the domain of the- Probability, Unsupervised machine learning, Linear Algebra, Exploratory data analysis, Calculus, Exploratory data analysis, Supervised machine learning, Statistics and Python. The Specialized Models: Time Series and Survival Analysis online course is being offered by IBM and is available on the platform of Coursera. The application fee for the course is free and the students will get to access the course guides after the process of registration. The programme certificate can be used by the students in their receptive CV and professional social media handles namely- LinkedIn, Monster India and others. The students in the course session will be guided and trained by professionals and industry experts.
Instructors
Mr Mark J Grover
Digital Content Delivery Lead
IBM
Mr Miguel Maldonado
Machine Learning Curriculum Developer
IBM
FAQs
Yes, deadlines are mandated for the applicants, but the students can also mould them. The deadlines are flexible.
Yes, in the Specialized Models: Time Series and Survival Analysis certification course the students will get to access subtitles.
For Specialized Models: Time Series and Survival Analysis training the students can get access to finances.
The Specialized Models: Time Series and Survival Analysis fee for the course is provided on the website.
The Specialized Models: Time Series and Survival Analysis certification is offered by IBM.
The students will be taking approximately 11 hours to complete the course on an online platform.
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