Comidoc Analysis
Learn how to use Python , Pandas, Numpy , and Statsmodels for Time Series Forecasting and Analysis!
Python for Time Series Data Analysis
InstructorJose PortillaDuration15h 21m
Students49.6K
Rating4.6 (8,830)
InstructorJose PortillaLearn how to use Python , Pandas, Numpy , and Statsmodels for Time Series Forecasting and Analysis!
InstructorJose PortillaEditorial course preview
These 2 complementary views highlight concrete, legible examples from the course presentation.
This slide introduces time series data analysis as a rapidly growing field in computer science, illustrated by a line chart showing increasing trends and seasonal patterns over several decades.
This slide highlights key Python libraries for time series analysis, displaying logos for Keras, StatsModels, and Prophet to illustrate the technical tools covered.
The curriculum covers a wide range of techniques, including statistical models like ARIMA/SARIMAX and Holt-Winters, alongside deep learning approaches using Keras and RNNs.
Instruction includes dedicated exercise segments for NumPy, Pandas, Statsmodels, and Keras to reinforce core concepts.
Learners have reported difficulty running notebooks and installing modules like Keras due to outdated library versions used in the recorded videos.
While some find the explanations concise, others report a lack of sufficient detail in the instruction.
The progression from Python basics to complex models aligns well with the target audience of developers.