We are happy to announce our new course in Approachable Data Science offered for beginners who have no exposure to machine learning or data science techniques in their background. There is no requirement to know a specific scripting or coding language or to have a computer science background. With this course we are sharing our skills to help teams struggling to add advanced analytics to their own digital products and customer facing web applications. Using a visual development environment, this instructor led course will show students how to setup a project, how to collect and prepare the data for machine learning and will walk through multiple examples of building models on real data in workshop style exercises. The students will leave having built their own models that learned the data and are able to classify, predict and forecast.
We saw a gap in the training that is available which led us to create something different and more exciting for beginners. Many other machine learning courses focus on a specific programming language and expect an audience with a background in software engineering. Those approaches wind up depending on programming language specific techniques and libraries that obfuscate the principled design and the best practices for a data science project. When a course decides to teach an aspect of machine learning project in the programming language python, either the class has to know the python or a substantial portion of the course needs to be dedicated to learning python.
Still, empowering teams to use these techniques is increasingly important. Customer expectations have evolved and customers expect more insightful, smarter and transparent services. They expect their own opportunity to analyze and explore the services they engage. They expect to be notified of problems before they arise, and to be guided toward better and more efficient uses of their services. They expect services to anticipate their needs and only the competitive ones will. This world has changed from one in which customers set the temperature on their thermostats to one in which the thermostat is expected to identify their ideal setting and anticipate their daily routine.
We want to help teams address this vital challenge without spending unnecessary time and energy on the tools. Our approach to this challenge is to use a visual machine learning workbench called KNIME. KNIME has been a trusted partner of Blacklight’s for nearly a decade and we consider our expertise in the tool a core competency. KNIME allows us to create machine learning processes that can be easily read and understood by a beginner, and carries out best practices at a high level rather than rummaging through the technical weeds. KNIME is an analyst favorite and consistently lands on the upper right of the Gartner Magic Quadrant for Data Science next to tools that, unlike KNIME, are not committed to open source. This approach has facilitated a course from which a diverse audience can gain expertise, including those who do not come to the course with a computer science or coding background. Most people who can use a spreadsheet will be comfortable with all of the concepts covered in the course and we are able to cover the fundamentals in a 2-day workshop. We look forward to seeing you there.