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Accounting Analytics (Coursera)

Accounting Analytics explores how financial statement data and non-financial metrics can be linked to financial performance. In this course, taught by Wharton's acclaimed accounting professors, you'll learn how data is used to assess what drives financial performance and to forecast future financial scenarios.

Managerial Accounting: Cost Behaviors, Systems, and Analysis (Coursera)

In this course, you will learn how to use accounting to facilitate and align decisions made by owners, managers, and employees. You will learn how accountants create, organize, interpret, and communicate information that improves internal processes, and allows organizations to identify and leverage opportunities to create value within the supply chain and with customers.

Data Visualization with Advanced Excel by PwC (Coursera)

In this course, you will get hands-on instruction of advanced Excel 2013 functions. You'll learn to use PowerPivot to build databases and data models. We'll show you how to perform different types of scenario and simulation analysis and you'll have an opportunity to practice these skills by leveraging some of Excel's built in tools including, solver, data tables, scenario manager and goal seek.

Machine Learning With Big Data (Coursera)

This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems.

Mathematical Biostatistics Boot Camp 1 (Coursera)

This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.

A Crash Course in Data Science (Coursera)

In this one-week class, we will provide a crash course in what these terms mean and how they play a role in successful organizations. This class is for anyone who wants to learn what all the data science action is about, including those who will eventually need to manage data scientists.

Data Science Math Skills (coursera)

This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus.

Machine Learning from Stanford University (Coursera)

This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).

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