Online courses directory (2)
Please note that the verified certificate option is not currently open for this course. Please enroll in the audit track and you will be emailed when the verified certificate option is open for enrollment.
Businesses, consumers, and societies leave behind massive amounts of data as a by-product of their activities. Leading-edge companies in every industry are using analytics to replace intuition and guesswork in their decision-making. As a result, managers are collecting and analyzing enormous data sets to discover new patterns and insights and running controlled experiments to test hypotheses.
This course, part of the Analytics: Essential Tools and Methods MicroMasters program, prepares you to understand data and business analytics and become a leader in these areas in business organizations.
It covers the methodologies, algorithms, issues, and challenges related to analyzing business data. It will illustrate the processes of analytics by allowing you to apply business analytics algorithms and methodologies to real-world business datasets from finance, marketing, and operations. The use of real-world examples and cases places business analytics techniques in context and teaches you how to avoid the common pitfalls, emphasizing theimportance of applying proper business analytics techniques.
In addition to cases, this course features hands-on experiences with data collection, analysis, and visualization using Python programs and analytics software such as SAS.
This course includes a significant analytics project.
Do you want to build systems that learn from experience? Or exploit data to create simple predictive models of the world?
In this course, part of the Data Science MicroMasters program, you will learn a variety of supervised and unsupervised learning algorithms, and the theory behind those algorithms.
Using real-world case studies, you will learn how to classify images, identify salient topics in a corpus of documents, partition people according to personality profiles, and automatically capture the semantic structure of words and use it to categorize documents.
Armed with the knowledge from this course, you will be able to analyze many different types of data and to build descriptive and predictive models.
All programming examples and assignments will be in Python, using Jupyter notebooks.
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