BOOTCAMP Forecasting

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Sln Topics
01 Introduction to time series and components of series models
02 Estimate simple forecasting methods such as arithmetic mean, random walk and random walk with drift
Approximate simple moving averages and exponential smoothing methods with no trends or seasonal pattern such as Brown simple exponential smoothing method
03 Approximate exponential smoothing methods with trend and seasonal patterns such as Holt-Winters additive, Holt-Winters multiplicative and Holt-Winters damped methods
04 Approximate exponential smoothing methods with trend and seasonal patterns such as Holt-Winters additive, Holt-Winters multiplicative and Holt-Winters damped methods
05 Stationary Series & Unit Root test
Dickey Fuellers & Augmented Dickey Fuellers Test
06 Importance of differencing
Trend differencing & Seasonal differencing
07 Auto correlation (ACF) and partial auto correlation functions (PACF)
08 Box Jenkins methods (ARIMA models)
09 Model diagnostics and residual analysis
Information criteria AIC, BIC, SIC
10 Models Forecasting Accuracy
11 Multivariate Time Series Modelling
12 Cointegrated Time Series Models
13 GARCH/ARCH Models for time varying volatility
14 Recurrent Neural Networks
15 Long Short Time Memory Neural Networks
ABOUT THE TRAINER

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Ans. 1. Anyone with finance background like having studied some level of CFA FRM or actuaries can join this program.

Ans.2. Maths Primers and Python Primers have been included in the program, so no previous experience is expected.

Ans 3. This course is quite long & comprehensive only because we have covered the entire curriculum in 3 parts – theory discussion, visualisations in excel, practical implementation through hands-on session in excel & python

Ans.4. To get certificates you need to complete all topic wise assignments, master project and pass the Final exam.

Ans.5. You can take either 1 year access or lifetime access. Please note that lifetime access is chargeable extra

Ans.6 With this website we have integrated a customized P2T player that will allow you to play encrypted classes. There are no limitations on the number of views. Also the software is compatible with Windows, Mac, Android or iPhone

Ans.7. To interact with the trainer we have a dedicated forum ‘D-forum’. Any questions asked on D-forum are expected to be replied within 24 hours by trainers and team of moderators & experts.

Ans. 8. Presently we are conducting exams in Aug mid and Jan mid. You can choose any of the cohort. In case you are not able to pass the exam in one go, you can re-book at a nominal charge

Ans.9. Every class is supported by One note files, Excel sheets & Python notebooks, Assignments and Quizzes, all these are available in the course section only.

Ans. 10. You get Letter of Recommendation physically delivered to you within 60 days of passing the exam. LOR’s also mention the chosen specialisation with the project details.

No content

Sln Topics
01 Introduction to time series and components of series models
02 Estimate simple forecasting methods such as arithmetic mean, random walk and random walk with drift
Approximate simple moving averages and exponential smoothing methods with no trends or seasonal pattern such as Brown simple exponential smoothing method
03 Approximate exponential smoothing methods with trend and seasonal patterns such as Holt-Winters additive, Holt-Winters multiplicative and Holt-Winters damped methods
04 Approximate exponential smoothing methods with trend and seasonal patterns such as Holt-Winters additive, Holt-Winters multiplicative and Holt-Winters damped methods
05 Stationary Series & Unit Root test
Dickey Fuellers & Augmented Dickey Fuellers Test
06 Importance of differencing
Trend differencing & Seasonal differencing
07 Auto correlation (ACF) and partial auto correlation functions (PACF)
08 Box Jenkins methods (ARIMA models)
09 Model diagnostics and residual analysis
Information criteria AIC, BIC, SIC
10 Models Forecasting Accuracy
11 Multivariate Time Series Modelling
12 Cointegrated Time Series Models
13 GARCH/ARCH Models for time varying volatility
14 Recurrent Neural Networks
15 Long Short Time Memory Neural Networks

No content

Ans. 1. Anyone with finance background like having studied some level of CFA FRM or actuaries can join this program.

Ans.2. Maths Primers and Python Primers have been included in the program, so no previous experience is expected.

Ans 3. This course is quite long & comprehensive only because we have covered the entire curriculum in 3 parts – theory discussion, visualisations in excel, practical implementation through hands-on session in excel & python

Ans.4. To get certificates you need to complete all topic wise assignments, master project and pass the Final exam.

Ans.5. You can take either 1 year access or lifetime access. Please note that lifetime access is chargeable extra

Ans.6 With this website we have integrated a customized P2T player that will allow you to play encrypted classes. There are no limitations on the number of views. Also the software is compatible with Windows, Mac, Android or iPhone

Ans.7. To interact with the trainer we have a dedicated forum ‘D-forum’. Any questions asked on D-forum are expected to be replied within 24 hours by trainers and team of moderators & experts.

Ans. 8. Presently we are conducting exams in Aug mid and Jan mid. You can choose any of the cohort. In case you are not able to pass the exam in one go, you can re-book at a nominal charge

Ans.9. Every class is supported by One note files, Excel sheets & Python notebooks, Assignments and Quizzes, all these are available in the course section only.

Ans. 10. You get Letter of Recommendation physically delivered to you within 60 days of passing the exam. LOR’s also mention the chosen specialisation with the project details.