Completely frustrated. They do not let the students know where the dataframes are, in order to be able to practice along the course. I searched on the course forum and there were other students asking the same questions. Where are the dataframes to practice?? No answer from anyone. I feel that I wasted my time.
Demand Forecasting Using Time Series

This course is the second in a specialization for Machine Learning for Supply Chain Fundamentals. In this course, we explore all aspects of time series, especially for demand prediction. We'll start by gaining a foothold in the basic concepts surrounding time series, including stationarity, trend (drift), cyclicality, and seasonality. Then, we'll spend some time analyzing correlation methods in relation to time series (autocorrelation). In the 2nd half of the course, we'll focus on methods for demand prediction using time series, such as autoregressive models. Finally, we'll conclude with a project, predicting demand using ARIMA models in Python.
Status: Matplotlib
Status: Forecasting
IntermediateCourse9 hours

All reviews
Showing: 15 of 15
All Learners
All Stars
Most Helpful
Michail Kritsotakis
1.0
Reviewed Sep 18, 2021Brandon Bartell
2.0
Reviewed Mar 9, 2022I took this course to learn ARIMA; however the instructor doesn't cover how the model works or how the hyperparameters affect it. They only talk about autoregression, not the integration or moving average comonents. Also the Jupyter notebooks that are used during the lecture are not available for download.
irem
2.0
Reviewed Jan 18, 2022The assignments are not clear and misleading. It asks an autocorrelation with a lag of 20, but the correct answer is the autocorrelation with a lag of 10. Also same video is uploaded in week 1 and week 2.
Sergey Kuper
1.0
Reviewed Dec 7, 2021Inconsistent, no feedback or answers to any questions at all
Sebastian Robledo
3.0
Reviewed Sep 27, 2021the assingment have some errors in the instuctions, the objectives described are not graded correctly
George Tanasa
1.0
Reviewed Jul 31, 2024Very bad course!! Double videos, bad programing labs( with wrong instructions vs expected results) not much discussion on results...just "push this button" instructions
Javier Aragón Navarro
1.0
Reviewed May 30, 2022Muy confuso con poca practica, creo que cuando el objetivo es programar es esencial tener los recursos para poder crear los códigos, .
SERDAR FINDIKCI
5.0
Reviewed Sep 13, 2022Great course to gain fundemantals of Time Series Analyses for Demand Forecasting..
Khoa Nguyen MT
5.0
Reviewed Nov 5, 2021I learnt a lot from this course.
Ittyavira C Abraham
5.0
Reviewed Nov 16, 2024Good but lab should be improved
LY NGUYỄN THỊ BÍCH
5.0
Reviewed Nov 25, 2024GOOD
Hediyeh Safari
4.0
Reviewed Mar 11, 2022I think it needs to complete more.
del Río, Silvia
3.0
Reviewed Oct 8, 2024One question in the final project is wrong
florence blandinieres
2.0
Reviewed Sep 20, 2021Nice tutorials for an introduction but absence of statistical tests to assess the characteristics of the time series at hands. Be careful in the assignments (one test set before the lesson on ARIMA for example). There are typos in the task description from the final assignment which can be misleading and very frustrating by dealing with the automatic script correction.
Juan Cruz Pistelli
2.0
Reviewed Aug 3, 2025There are major mistakes with the grading system and this module doesn't let me finish the course. Terrible.
Show: 20 results per page