|//No Comment - New Coursera Specializations|
|Saturday, 24 September 2016|
Coursera has some new Computer Science and Data Science specializations ready to roll from next week.
Sometimes the news is reported well enough elsewhere and we have little to add other than to bring it to your attention.
No Comment is a format where we present original source information, lightly edited, so that you can decide if you want to follow it up.
The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have basic a python or programming background, and want to apply statistical, machine learning, information visualization, and text analysis techniques to gain new insight into their data.
Introduction to Data Science with Python (course 1),
Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate.
This Specialization covers R software development for building data science tools. As the field of data science evolves, it has become clear that software development skills are essential for producing useful data science results and products. You will obtain rigorous training in the R language, including the skills for handling complex data, building R packages and developing custom data visualizations. You will learn modern software development practices to build tools that are highly reusable, modular, and suitable for use in a team-based environment or a community of developers.
You will also have demonstrated this fluency through an in-depth Capstone Project that can be shown to prospective employers in the fast-growing field of UI design.Concepts and techniques covered include structured approaches for helping you understand your user base and their needs (e.g. contextual inquiry and design psychology), widely-employed prototyping and design methods (e.g. low-fidelity and paper prototyping), and robust techniques for helping you evaluate your design choices (e.g. heuristic evaluation and user studies). By the end of the Specialization, you will be comfortable applying these concepts and techniques to design an interface for a wide variety of users from around the world.
Products and business models in today's competitive environment are increasingly being transformed by technology. This new digital economy places IT at the centre of firm strategy and operations, and requires a new breed of IT managers and leaders who can examine technology through a business lens. The Business Technology Management specialization will empower you with knowledge of the IT domain, management, leadership and team building skills, and functional and analytical skills. These skills are critical to leverage technology to create competitive advantage.
In 2020 the world will generate 50 times the amount of data as in 2011. And 75 times the number of information sources (IDC, 2011). Being able to use this data provides huge opportunities and to turn these opportunities into reality, people need to use data to solve problems.
This Specialization, in collaboration with Tableau, will teach you to generate powerful reports and dashboards that will help people make decisions and take action based on their business data. You will use Tableau to create high-impact visualizations of common data analyses to help you see and understand your data. You will apply predicative analytics to improve business decision making. The Specialization culminates in a Capstone Project in which you will use sample data to create visualizations, dashboards, and data models to prepare a presentation to the executive leadership of a fictional company.
The Data Analytics for Business Specialization brings together academic professionals and experienced practitioners to share real world data analytics skills you can use to grow your business, increase profits, and create maximum value for your shareholders. Learners gain practical skills in extracting and manipulating data using SQL code, executing statistical methods for descriptive, predictive, and prescriptive analysis, and effectively interpreting and presenting analytic results.
In this specialization you will learn how to
:• Find, extract, organize and describe data to support business decisions
• Identify, quantify and interpret relationships between variables
• Derive customer insights from your data
• Develop spreadsheet models to analyze data, evaluate risk and optimize business decisions
• Present and justify a course of action to managementThe capstone project will give you an opportunity to apply what has been covered in the specialization to solve a marketing analytics problem.
The Business Statistics and Analysis Specialization is designed to equip you with a basic understanding of business data analysis tools and techniques. You’ll master essential spreadsheet functions, build descriptive business data measures, and develop your aptitude for data modeling. You’ll also explore basic probability concepts, including measuring and modeling uncertainty, and you’ll use various data distributions, along with the Linear Regression Model, to analyze and inform business decisions. The Specialization culminates with a Capstone Project in which you’ll apply the skills and knowledge you’ve gained to an actual business problem.
This specialization covers all the fundamental techniques in recommender systems, from non-personalized and project-association recommenders through content-based and collaborative techniques. Designed to serve both the data mining expert and the data literate marketing professional, the courses offer interactive, spreadsheet-based exercises to master different algorithms along with an honors track where learners can go into greater depth using the LensKit open source toolkit. A capstone project brings together the course material with a realistic recommender design and analysis project.
or email your comment to: firstname.lastname@example.org
|Last Updated ( Sunday, 25 September 2016 )|