Generative AI for Business Leaders
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How Google does Machine Learning
Our Courses
The Econometrics of Time Series Data
In this course, you will look at models and approaches that are designed to deal with challenges raised by time series data. The discussion covers the motivation for the use of particular models and the description of the characteristics of time series data, with a special attention raised to the potential memory. You will: – Discuss time series models, that refer to data that have been collected over a period on one or more variables for the same individual.
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Course by
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Self Paced
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31 hours
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English
Machine Learning for Accounting with Python
This course, Machine Learning for Accounting with Python, introduces machine learning algorithms (models) and their applications in accounting problems. It covers classification, regression, clustering, text analysis, time series analysis. It also discusses model evaluation and model optimization. This course provides an entry point for students to be able to apply proper machine learning models on business related datasets with Python to solve various problems. Accounting Data Analytics with Python is a prerequisite for this course.
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Course by
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Self Paced
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64 hours
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English
Judgmental Business Forecasting in Excel
In this course, we extend your business forecasting expertise from the first two courses of our Business Forecasting Specialisation on Time Series Models and Regression Models. We will explore the role of judgmental forecasting, when more quantitative forecasting methods have limitations, and we need to generate further business insights. We will be exploring some structured methodologies to create judgmental business forecasts using Business Indicators, Subjective Assessment Methods, and Exploratory Methods.
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Course by
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Self Paced
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10 hours
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English
Compare time series predictions of COVID-19 deaths
By the end of this project, you will learn how to perform the entire time series analysis workflow for the daily COVID-19 deaths.
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Course by
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Self Paced
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2 hours
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English
Creating Features for Time Series Data
This course focuses on data exploration, feature creation, and feature selection for time sequences. The topics discussed include binning, smoothing, transformations, and data set operations for time series, spectral analysis, singular spectrum analysis, distance measures, and motif analysis. In this course you learn to perform motif analysis and implement analyses in the spectral or frequency domain.
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Course by
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Self Paced
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8 hours
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English
Policy Analysis Using Interrupted Time Series
A comprehensive course on conducting and presenting policy evaluations using interrupted time series analysis.
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Course by
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Self Paced
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English
Analyzing the Universe
Using publicly available data from NASA of actual satellite observations of astronomical x-ray sources, we explore some of the mysteries of the cosmos, including neutron stars, black holes, quasars and supernovae. We will analyze energy spectra and time series data to understand how these incredible objects work.
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Course by
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Self Paced
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22 hours
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English
Sequences, Time Series and Prediction
If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In this fourth course, you will learn how to build time series models in TensorFlow. You’ll first implement best practices to prepare time series data. You’ll also explore how RNNs and 1D ConvNets can be used for prediction.
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Course by
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Self Paced
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23 hours
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English
Data Visualization
In the era of big data, acquiring the ability to analyze and visually represent “Big Data” in a compelling manner is crucial. Therefore, it is essential for data scientists to develop the skills in producing and critically interpreting digital maps, charts, and graphs. Data visualization is an increasingly important topic in our globalized and digital society. It involves graphically representing data or information, enabling decision-makers across various industries to comprehend complex concepts and processes that may otherwise be challenging to grasp.
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Course by
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Self Paced
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16 hours
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English
Applied AI with DeepLearning
>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area
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Course by
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Self Paced
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25 hours
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English