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Starts : 2017-12-01
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edX Free Closed [?] English AdelaideX Computer Science Data Analysis & Statistics EdX

Gain essential skills in today’s digital age to store, process and analyse data to inform business decisions.

In this course, part of the Big Data MicroMasters program, you will develop your knowledge of big data analytics and enhance your programming and mathematical skills. You will learn to use essential analytic tools such as Hadoop, R and MOA (Massive Online Analysis).

Topics covered in this course include:

  • cloud-based big data analysis;
  • predictive analytics, including probabilistic and statistical models;
  • application of large-scale data analysis;
  • analysis of problem space and data needs;
  • understanding of ethical and social concerns of data mining.

By the end of this course, you will be able to approach large-scale data science problems with creativity and initiative.

Starts : 2017-12-11
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edX Free Closed [?] English Business & Management ColumbiaX EdX

This course is about modeling and how computer models can support managerial decision making. A model is a simplified representation of a real situation and modeling is the process of developing, analyzing and interpreting a model in order to help make better decisions. Models can be invaluable tools in managing and understanding the complexity and risk inherent in many business problems. As a result, models have become an increasingly important part of business at all levels from daily operations to strategic decision making.

This course will help learners become intelligent users and consumers of these models. To this end, we will cover the basic elements of modeling – how to formulate a model and how to use and interpret the information a model produces. The course emphasizes “learning by doing” so that students will be expected to formulate, solve, and interpret a number of different optimization and simulation models using Excel spreadsheets. An important theme in the course is to understand the appropriate use of models in business and the potential pitfalls from using models incorrectly or inappropriately.

The course has two distinct parts:

  • The first half of the course we will cover supervised learning techniques for regression and classification. In this framework, we possess an output or response that we wish to predict based on a set of inputs. We will discuss several fundamental methods for performing this task and algorithms for their optimization. Our approach will be more practically motivated, meaning we will fully develop a mathematical understanding of the respective algorithms, but we will only briefly touch on abstract learning theory.
  • In the second half, we shift to unsupervised learning techniques. In these problems the end goal less clear-cut than predicting an output based on a corresponding input. We will cover three fundamental problems of unsupervised learning: data clustering, matrix factorization, and sequential models for order-dependent data. Some applications of these models include object recommendation and topic modeling.

Starts : 2017-12-11
No votes
edX Free Closed [?] English Business & Management ColumbiaX EdX

Marketers want to understand and forecast how customers purchase products and services and how they respond to marketing initiatives.

Learn how analytics help businesses drive marketing to maximize its effectiveness and optimize return on investment (ROI).

In this course, part of the Business Analytics MicroMasters program, discover how to develop quantitative models that leverage business data, statistical computation, and machine learning to forecast sales and marketing impact for:

  • customer relationship management;
  • market segmentation;
  • value creation;
  • communication;
  • monetization.

You will learn how to use probabilistic models and optimization tools to model customer demand forecasts, pricing sensitivity, Lifetime Value and how to leverage such data to make optimal decisions on designing new products, marketing segmentation and strategy.

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