By Kyle Clark, Senior Skills Transformation Consultant
Coursera released 50+ courses on our platform in October. This month brings a number of new courses focused on innovation and disruption, from developing a systems mindset to digital transformation, AI workflows, and futures thinking.
Here are our top picks for enterprise for this past month:
October 2019’s Key Launches:
- Developing a Systems Mindset, University of Colorado Boulder – This course will highlight the urgency for you to have a systems mindset to engage complex problems for a systems perspective, meaning that you have approach problems from different angles, scales and perspectives. This class is the first step in creating that mindset and for you to effectively engage – from receiving the “ask” for “assistance”, to orienting yourself to the issue, understanding the community, and developing a project plan.
- Impact from Digital Transformation: Full course, EIT Digital – This course is about what you can do when everything around you seems to be moving due to digital change. It is about how to handle the disruptive process that tends to unfold in industry nowadays due to digitalisation. The way to handle this is what is here referred to as “Digital Transformation” and at the core of it, it is about understanding how the new business landscape is evolving and heading for a new position in that landscape. It is about corporate strategy.
- IBM AI Enterprise Workflow Specialization, IBM – This six course specialization is designed to prepare you to take the certification examination for IBM AI Enterprise Workflow V1 Data Science Specialist. IBM AI Enterprise Workflow is a comprehensive, end-to-end process that enables data scientists to build AI solutions, starting with business priorities and working through to taking AI into production. After successfully completing this specialization, you will be ready to take the official IBM certification examination for the IBM AI Enterprise Workflow.
- Exploratory Data Analysis with MATLAB, MathWorks – In this course, you will learn to think like a data scientist and ask questions of your data. These skills are valuable for those who have domain knowledge and some exposure to computational tools, but no programming background is required.
- Futures Thinking Specialization, Institute for the Future – Do you want to think about the future with more creativity and optimism? Do you want to see what’s coming faster, so you can be better prepared for disruptions and more in control of your future? This Specialization will introduce you to the practice of futures thinking, as developed and applied for the past 50 years by the Institute for the Future, a Silicon-Valley-based research and learning group founded in 1968. The Futures Thinking specialization is for anyone who wants to spot opportunities for innovation and invention faster.
- Machine Learning for All, University of London – In this course you will learn to understand the basic idea of machine learning, even if you don’t have any background in math or programming. You might be a manager or other non-technical role in a company that is considering using Machine Learning. You really need to understand this technology, and this course is a great place to get that understanding.
|Strategies for Effective Engagement||University of Colorado Boulder|
|Transforming Communities||University of Colorado Boulder|
|Contexto de Negocios en LATAM: Factores Políticos, Sociales y Económicos||Pontificia Universidad Católica de Chile|
|3D Printing Hardware||University of Illinois at Urbana-Champaign|
|Закон стартапа: юридические основы технологического бизнеса||Moscow Institute of Physics and Technology|
|Formulación y evaluación de proyectos complejos||Universidad de los Andes|
|Business Implications of AI: A Nano-course||EIT Digital|
|الذكاء الاصطناعي للجميع||deeplearning.ai|
|Business Implications of AI: Full course||EIT Digital|
|القيادة والذكاء العاطفي||Indian School of Business|
|Искусство продаж||Saint Petersburg State University|
|Impact from digital transformation: A Nano course||EIT Digital|
|Data for Machine Learning||Alberta Machine Intelligence Institute|
|Become a CBRS CPI at WISPAPALOOZA||Google – Spectrum Sharing|
|AI Workflow: Business Priorities and Data Ingestion||IBM|
|AI Workflow: Data Analysis and Hypothesis Testing||IBM|
|AI Workflow: Feature Engineering and Bias Detection||IBM|
|Project: Data Analysis in R with dplyr||Rhyme|
|Distributed Computing with Spark SQL||University of California, Davis|
|Improving Your Statistical Questions||Eindhoven University of Technology|
|Project: Multiple Linear Regression with scikit-learn||Rhyme|
|Project: Predict Sales Revenue with scikit-learn||Rhyme|
|Project: Predicting House Prices with Regression using TensorFlow||Rhyme|
|Project: Basic Image Classification with TensorFlow||Rhyme|
|Enjoyable Econometrics||Erasmus University Rotterdam|