Once the purview of programmers and statisticians, machine learning has expanded across applications and disciplines into virtually every industry. And to keep pace with an increasingly data-driven marketplace, professionals of all stripes have set their sights on mastering its fundamentals.
UC Berkeley Extension’s Practical Machine Learning course offers a hands-on introduction to machine learning with R-programming that includes real-world datasets that let you solve problems in a variety of industries. Whether it’s business leaders aiming to improve their understanding of data science and machine learning to coordinate better with teams on tactical data-based initiatives, or aspiring data scientists seeking to master the practical aspects of problem framing and model deployment, the course addresses topics, tools, and techniques to help professionals from any background or industry enhance their machine learning skills.
At the end of this course, participants will learn to:
Emeritus and UC Berkeley Extension
UC Berkeley Extension is collaborating with online education provider Emeritus to offer a portfolio of high-impact online courses. These courses leverage UC Berkeley’s thought leadership in technical practice developed over years of research, teaching, and practice. By collaborating with Emeritus, we are able to broaden access beyond our on-campus offerings in a collaborative and engaging format that stays true to the quality of UC Berkeley. Emeritus’ approach to learning is formulated on a cohort-based design to maximize peer-to-peer sharing and includes live teaching with world-class faculty and hands-on project-based learning. In the last year, more than 30,000 students from over 120 countries have benefited professionally from Emeritus.
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Participants will get an introduction to unsupervised learning algorithmic techniques, such as K-means and hierarchical clustering. and employ clustering techniques to develop segments from customer data.
Participants will get an introduction to neural networks and make predictions based upon a dataset with information on office supply purchases.
Participants will apply logistic regression to a dataset including features on credit card users and develop a model predicting the probability of default payments based upon previous payment history, bill amount, and customer demographics.
Participants will examine classification problems and apply what they have learned to an employee attrition data set in order to make predictions about the probability of an employee leaving his/her company.
Participants will perform an exploratory data analysis (EDA) and build a univariate or multivariate linear regression model using data from Apple’s app store.
Participants will walk through practical examples of problem framing and identify approaches to modeling customer lifetime value and develop recommendation engines.
Adjunct Professor in UC Berkeley’s Department of Computer Science and a Founding Partner of Decision Patterns
Course Instructor, Emeritus
Emeritus follows a unique online model. This model has ensured that nearly 90 percent of our learners complete their course.
Orientation WeekThe first week is orientation week. During this week you will be introduced to the other participants in the class from across the world. You will also learn how to use the learning platform and other learning tools provided.
Weekly GoalsOn other weeks, you have learning goals set for the week. The goals would include watching the video lectures and completing the assignments. All assignments have weekly deadlines.
Recorded Video LecturesThe recorded video lectures are by faculty from the collaborating university.
Live WebinarsEvery few weeks, there are live webinars conducted by Emeritus course leaders. Course leaders are highly-experienced industry practitioners who contextualize the video lectures and assist with questions you may have regarding your assignments. Live webinars are usually conducted between 1 pm and 3 pm UTC on Tuesdays and Wednesdays.
Clarifying DoubtsIn addition to the live webinars, for some courses, the course leaders conduct Office Hours, which are webinar sessions that are open to all learners. During Office Hours, learners ask questions and course leaders respond. These are usually conducted every alternate week to help participants clarify their doubts pertaining to the content.
Follow-UpThe Emeritus Program Support team members will follow up and assist over email and via phone calls with learners who are unable to submit their assignments on time.
Continued Course AccessYou will continue to have access to the course videos and learning material for up to 12 months from the course start date.
Assignments are given out weekly and they are based on the lectures or tutorials provided. They need to be completed and submitted as per the deadline for grading purposes. Extensions may be provided based on a request sent to the support team.
It is an open forum where participants pin their opinions or thoughts regarding the topic under discussion.
Emeritus Program Support Team
If at any point in the course you need tech, content or academic support, you can email program support and you will typically receive a response within 24 working hours or less.
You can access Emeritus courses on tablets, phones and laptops. You will require a high-speed internet connection.
On completing the course you join a global community of 5000+ learners on the Emeritus Network. The Network allows you to connect with Emeritus past participants across the world.
For any questions regarding Emeritus, the learning experience, admission & fees, grading & evaluation please visit COMMON FAQs
Special pricing up to 20% discount is available if you enroll with your colleagues.