Algorithms are the foundations for big data analytics. Build upon the skills acquired in Applied Statistics and Business Insights to build a stronger foundation across organizing, sorting, and searching data and, most importantly, recommendation engines.

Communication and Collaboration #2 builds on your skills developed in Module 1. You'll focus on individual effectiveness in team settings as well as team interaction, conflict resolution and negotiation, and decision-making.

Inform yourself on the principles and techniques of computer programming using R as well as a variety of numerical and computational problems. You’ll also learn how to program and use R for effective data analysis for large datasets. Explore real examples of practical issues in statistical computing, including programming in R.

While data is critical for making well-informed decisions, how you present data to stakeholders can make the difference between a new or improved business model and a missed opportunity. This course covers the design concepts involved in visualizing data for decision-makers. You’ll use market-ready tools to perform ETL processes and create storytelling using data visualization tools.

Experimental design is a fundamental data-driven approach to making good business decisions. Gain an understanding of probability, inference, comparison, and regression techniques. Learn how to recognize and understand each business question, use statistical tools to conduct analysis, and communicate results clearly and concisely.

This business challenge will enhance your quantitative thinking. You’ll work in teams with real datasets to frame a business problem, researching supplemental data and news to support your solution. You’ll then use data wrangling and cleaning techniques to establish a hypothesis, before using modeling concepts to produce recommendations.