The Applied Machine Learning course teaches you a wide-ranging set of techniques of supervised and unsupervised machine learning approaches using Python as the programming language.
Since this course requires an intermediate knowledge of Python, you will spend the first part of this course learning Python for Data Analytics taught by Emeritus. This will provide you with the programming knowledge required to do the assignments and application projects that are part of the Applied Machine Learning course.
If you are looking to implement or lead a machine learning project or looking to incorporate machine learning capability in your software application, this course is appropriate for you. This is a programming course: you will be required to write code, but no prior programming knowledge is required.
PREREQUISITES:
The course requires an undergraduate knowledge of statistics (descriptive statistics, regression, sampling distributions, hypothesis testing, interval estimation etc.), calculus (derivatives), linear algebra (vectors & matrix transformation) and probability (conditional probability/Bayes theorem).
*Assessment: Students will be given an assessment to test their math skills prior to commencement of the course. You can view sample questions by clicking here. To familiarize yourself with the topics of the assessment, refer to learning resources by clicking here.
240+ Faculty Video Lectures
45 Quizzes / Assignments
18 Moderated Discussion Boards
20+ Q&A Sessions with Course Leaders
12 Application Projects
Includes Live Online Teaching
Going beyond the theory, our approach invites participants into a conversation, where learning is facilitated by live subject matter experts and enriched by practitioners in the field of machine learning:
Define a model for your data and make the model learn.
Build regression models to predict an unknown output from a given set of inputs.
Create classification models to categorize datasets such as email messages as spam or non-spam.
Develop unsupervised models like topic models or recommender systems to extract hidden patterns from large amounts of data
Determine hidden parameters in data to improve the accuracy of your model's predictions.
Create probabilistic data models to predict a range of possible outcomes that account for real-world risks and uncertainties.
Designed to teach you models and methods used in machine learning for real-world applications such as recommender systems and classification models, this 5-month program begins by building your foundational skills in Python, followed by the supervised and unsupervised learning techniques of applied machine learning.
Columbia University Associate Professor, Electrical Engineering Affiliated Member, Data Sciences Institute
John has a PhD from Duke and has been a postdoctoral researcher in the Computer Science departments at Princeton University and UC Berkeley. John Paisley’s research focuses on...
Upon successful completion of the course, participants will receive a verified digital certificate from Emeritus in collaboration with Columbia Engineering Executive Education.
For each referral when you invite colleagues to the program.
Upskill with a program from a top university
Leverage cohort-based learning, for high completion rates
Many organizations have historically sponsored their employees for our executive education programs. Please check with your employer if they can cover your fee. We can assist you with the necessary documentation and support.
Preparing Your Pitch
If you require company approval, we offer a customizable email template that you can use to show how the program will contribute to your growth.
Invoice Requirements
An invoice will be issued to you after payment. If you require any customization, our advisory team can assist you.
Part/Full Sponsorship
Our advisors are here to support you throughout the reimbursement process, whether your company covers the fee fully or partially.
Additional Questions
Should your employer require specific information to approve your reimbursement, our advisory team is well-equipped to help you.
Didn't find what you were looking for? Write to us at learner.success@emeritus.org or Schedule a call with one of our Program Advisors or call us at +1 315 840 3227 (US) / +44 203 838 0797 (UK) / +65 3129 4176 (SG)
Flexible payment options available.
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