Applied Machine Learning

ONLINE CERTIFICATE COURSE

Machine Learning has become an entrenched part of everyday life. The books we buy, the movies we watch, the sports we follow, the driving directions we get are driven by Machine Learning algorithms. It is one of the most exciting fields of computing today. And Machine Learning practitioners are in high demand, with a shortfall of 250,000 data scientists forecast.

At Columbia Engineering, we are fascinated by the possibilities of Machine Learning. We have created the Applied Machine Learning course, in partnership with EMERITUS, to help students across the world apply Machine Learning to improve every aspect of human life.

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.

COURSE HIGHLIGHTS

  • Faculty Video Lectures
  • Peer Learning
    Moderated Discussion Boards
  • assignment icon
    Quizzes/Assignments
  • Real World Applications
    Application Projects
  • Q&A Sessions with Course Leaders
  • webinar
    Live Online Teaching

SYLLABUS

SUPERVISED LEARNING

Maximum Likelihood, Least Squares, Regularization

Bayes Rule, MAP Inference, Active Learning

Nearest Neighbors, Perceptron, Logistic Regression

Kernel Methods, Gaussian Process

SVM, Trees, Forests and Boosting

UNSUPERVISED LEARNING

K-Means Clustering, E-M, Gaussian Mixtures

Collaborative Filtering, Topic Modeling, PCA

Markov and Hidden Markov Models, Kalman Filters

Model Comparisons, Analysis Considerations

APPLICATION PROJECTS

Movie Recommendation Engine

Movie Recommendation Engine

You will build a movie recommendation engine by applying collaborative filtering and topic modelling techniques. You use a dataset which contains 20 million viewer ratings of 27,000 movies.

House Price Prediction

House Price Prediction

You will write code to predict house prices based on several parameters available in the Ames City dataset compiled by Dean De Cock using least squares linear regression and Bayesian linear regression.

Human Activity Prediction

Human Activity Prediction

You will predict the human activity (walking, sitting, standing) that corresponds to the accelerometer and gyroscope measurements by applying the nearest neighbours technique.

Credit Card Fraud Detection

Credit Card Fraud Detection

You will detect potential frauds using credit card transaction data. You will apply the random forest method to identify fraudulent transactions.

Marketing Segmentation

Marketing Segmentation

You will create market segments using the US Census dataset and by applying the k-means clustering method.

FACULTY

  • John Paisley
    John Paisley
    Columbia University Associate Professor, Electrical Engineering Affiliated Member, Data Sciences Institute.
    Columbia Engineering Executive Education

LEARNING EXPERIENCE

EMERITUS follows a unique online model. This model has ensured that nearly 90 percent of our learners complete their course.

  • OrientationOrientation Week
    The 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 management system and other learning tools provided.
  • Goal SettingWeekly Goals
    On 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.
  • Video LecturesRecorded Video Lectures
    The recorded video lectures are by David Rogers, Faculty at Columbia Business School.
  • Live WebinarsLive Webinars
    Every 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 DoubtsClarifying Doubts
    In addition to the live webinars, the course leaders also 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 conducted every alternate week to help participants clarify their doubts pertaining to the content.
  • Follow-UpFollow-Up
    The EMERITUS program support team follow-up and assist over email and phone calls with learners who are unable to submit their assignments on time.
  • Continuous Course AccessContinued Course Access
    You will continue to have access to the course videos and learning material for up to 12 months from the course start date.

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.

 

Device Support

You can access EMERITUS courses on tablets, phones and laptops. You will require a high-speed internet connection.

 

EMERITUS Network

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.

ADMISSION & FEES

DURATION AND COURSE FEE

  • Starts 27 March 2019
  • 3 Months
  • 6 – 8 hours per week
  • Course Fees USD 1200

PRE-REQUISITES

The course requires an undergraduate knowledge of statistics, (descriptive statistics, regression, sampling distributions, hypothesis testing, interval estimation, etc.) calculus, linear algebra, and probability.

You should be comfortable with Python or any other programming language. All assignments/application projects will be done using the Python programming language using one or more of the following packages pandas, NumPy, Matplotlib, seaborn, scikit-learn, PyMC3 etc.

PAYMENT

  • You can pay for the course either with an international debit or credit card, or bank wire transfer. On clicking the apply now button, you will be directed to the application form and the payment page.
  • We provide deferrals and refunds in specific cases. The deferrals and refund policy is available here.
  • You will be provided a course login within 48 hours of making a payment.

APPLICATION PROCESS

  • Please provide your work experience and your current employer via the application.
  • You can apply by clicking the Apply Now button

COURSE FAQs

FAQs that are specific to this course are below. If you have questions regarding Emeritus, the learning experience, admission & fees,  grading & evaluation please visit CERTIFICATE PROGRAM FAQs

WHO IS THIS COURSE DESIGNED FOR?

Machine Learning has become an entrenched part of everyday life. The books we buy, the movies we watch, the sports we follow, the driving directions we get are driven by Machine Learning algorithms. It is one of the most exciting fields of computing today, and Machine Learning practitioners are in high demand.

Scientist, Machine Learning Engineer, Business Analyst – Machine Learning, Machine Learning Project Lead, etc.

This course is designed for professionals currently in or seeking to secure a position as a:

This course is designed for professionals currently in or seeking to secure a position as a:

  • Data Analyst
  • Business Analyst
  • Statistician/Mathematician
  • Data Scientist
  • Data Engineer
  • Big Data Engineer
  • Software Developer

The course familiarizes you with Machine learning algorithms and applications. It will also help you understand the approach to a business problem and provide you with the tool knowledge needed to transition to a Machine Learning or a Data Science role.

The course familiarizes you with Machine learning algorithms and applications. It will also help you understand the approach to a business problem and provide you with the tool knowledge needed to transition to a Machine Learning or a Data Science role.

The course familiarizes you with Machine learning algorithms and applications and provides a solid foundation in statistics/mathematics and problem-solving skills to help you solve enterprise-level problems. The Applied Machine Learning course augments your existing knowledge of various tools and expands your skill set as a Data Science or Machine Learning professional.

The course familiarizes you with Machine learning algorithms and applications while providing a solid foundation in statistics/mathematics and enhancing your business acumen. It augments your existing programming knowledge and expands the technologies you are familiar with, helping you further develop your skill set as a Data Science or Machine Learning professional.

Absolutely! Knowledge of Data Science and Machine Learning (ML) has quickly become a requisite across industries, and all businesses will eventually need to use these techniques to thrive. While your current role may not require Machine learning knowledge, it is almost certain that ML skills will be in high demand in most every industry in the future.

The Applied Machine Learning course is an intensive, 12-week online certificate course designed for working professionals seeking to develop advanced skills in Data Science and Machine Learning. The certificate is awarded by EMERITUS in collaboration with Columbia Engineering Executive Education.

This course is designed for working professionals looking to gain skills in advanced concepts in Machine Learning, like Supervised and Unsupervised learning. This course demands consistent work and a time commitment of six to eight hours per week during the 12-week course.

This course is NOT intended to provide superficial Machine Learning concepts. Rather, the course delves deeper and is aimed at developing professionals who can advance their careers as practitioners in Data Science and Machine Learning roles.

The course evaluates two core pillars of Machine Learning: Supervised Learning and Unsupervised Learning. These two focus areas will cover concepts including Regression, Bayesian Methods, Foundational Classification Algorithms, Refinements to Classification, Intermediate Classification Algorithms, Clustering Methods, Recommendation Systems, Sequential data Models, and Association Analysis. The topics are woven together to provide a comprehensive perspective on applied Machine Learning.

The course is a combination of interactive lectures and individual and team assignments. It also includes live sessions with course leaders dedicated to guiding you through your learning journey.

The Applied Machine Learning certificate program comprises of ten (10) modules spanning across three (3) months duration. The course has fixed start and end dates. To complete the program, students must successfully complete all the modules and the associated video lectures, assignments & application projects. The projects require learners to apply the Machine Learning concepts they have learned to datasets and derive inferences. In addition to this, participant would be exposed to discussions and live webinars where learning is facilitated by subject matter experts and enriched by practitioners in the field of machine learning.

The course is a blend of theory, tools, and case studies (datasets) that are easy to assimilate and implement. For instance, students work on application projects that require them to apply the Machine Learning concepts they’ve learned to datasets and derive inferences. These application projects are intentionally made to be challenging, and students are expected to spend substantial time and effort solving them; likely eight to 10 hours per week. At the end of the course, students will be able to apply Machine Learning to solve many of the business problems they face in their workplace.

Yes, EMERITUS offers need-based scholarships for a limited number of participants. Please note: A complete and accurate application for the course is required to be considered for a scholarship. Once your application has been reviewed, you’ll be notified about any scholarship you may be eligible for.

Columbia Engineering Executive Education is collaborating with online education provider EMERITUS Institute of Management to offer a portfolio of high-impact online courses. These courses leverage Columbia’s thought leadership in management practice developed over years of research, teaching, and practice.

The course requires prior exposure to calculus, linear algebra and probability. Familiarity with a programming language is also required.

ADMISSIONS

Yes, you must apply to enroll in the course by completing a short application form. This certificate course accepts all applicants regardless of experience and specific background.

No, this certificate course accepts all applicants regardless of experience and specific educational background.

No, this certificate course accepts all applicants regardless of experience and specific educational background.

The course does not accrue any credits or education points toward any courses from Columbia University.

You can pay for the course using an International Debit or Credit card. Alternatively, you can also pay for the program using Bank/Telegraphic transfer mechanism. Please find below the Telegraphic transfer details (please quote the Invoice No):
Account Name: Emeritus Institute of Management Pte Ltd
Bank Name: The Hongkong and Shanghai Banking Corporation Limited
Bank Address: 21 Collyer Quay, #07-01 HSBC Building, Singapore 049320
USD Account Number: 260-816558-178
Bank Code: 7232
Branch Code: 260
SWIFT Code: HSBCSGSG
Once you complete the application for the course, you will receive an invoice. Payment for the course is required to gain access. You will be given a receipt once the payment is received for your files and/or tax purposes.

LEARNING / TEACHING / GRADING / CERTIFICATE

What software and versions will I need in this course?

  • Processors: 2.60 GHz
  • RAM: 8 GB of RAM
  • Disk space: 2 to 3 GB
  • Operating systems: Windows 10, MacOS and Linux
  • Python download link
  • Compatible tools: Any text editor, Command prompt

Minimum System Requirements

  • Processors: 1 GHz
  • RAM: 1 GB of RAM
  • Disk space: 1 GB
  • Operating systems: Windows 7 or later, MacOS and Linux
  • Python versions: 2.7.X, 3.6.X
  • Compatible tools: Any text editor, Command prompt

You will lose access to the content of the Certificate Course if you fail to graduate within the fixed duration of the course. Only students who successfully complete the course retain access to the course contents.

No. The start and end dates of this course are fixed, and you must complete all assignments by the end of the course. There is some opportunity to work at your own pace within this framework, but following our recommended timeline is the best way to ensure you’re able to keep pace with your peers and complete the course on time.

No. Due to the fixed-term nature of this certificate, and the need for maintaining a consistent and stable student body throughout, you do not have the option to pause and resume the course later.

Upon successful completion of the course, participants will be awarded a verified digital certificate by EMERITUS Institute of Management, in collaboration with Columbia Engineering Executive Education.

You will receive a Soft copy of the certificate post successful completion of the course.

Live teaching sessions are usually scheduled between 9 a.m. and 10 a.m. Eastern time. All live teaching sessions are recorded and shared with students within 24 hours. The recording links are also made available on the EMERITUS Learning Platform (Canvas).

There will be live sessions conducted by industry experts during the course. The number of sessions varies from cohort to cohort as per the course flow.

It will require at least 6–8 hours dedicated learning per week to optimally benefit from the program.

If students have technical questions or need to request for assignment extension, they can contact the Course Coordinator via a ticketing system integrated into the EMERITUS Learning Platform. Students can also contact Course Leaders via the EMERITUS Learning Platform Inbox to get clarification on any content-related questions.

All course materials can be accessed through the EMERITUS Learning Portal at student.emeritus.org. Once you have enrolled in the course and logged into the learning platform, instructions for the course and assignment submissions will be provided.  All assignments will be submitted online through the learning portal.

The course is rolled out in a specific structure and sequence to ensure the optimal user experience. There are many assignments interspersed at specific points in the course to facilitate the best learning experience. Moving ahead to view videos without completing these assignments would negatively affect the course’s prescribed learning experience.

You will have access to all the course materials, including the videos, for a period of 12 months from the day your course began.

Our content licensing agreements with our university partners and world-class faculty restrict us from allowing videos to be downloaded. This step is necessary to protect the integrity of the course, our university partners’ brands, and the personal brand of our faculty.

Beyond internet access, everything you need will be provided via the course platform.

There are no exams, but there are assignments at the end of most modules to help you apply what you’ve learned.

This course is 12 weeks long, with each week including some or all the following activities:

  • Video Lectures
  • Additional Reading
  • Case Studies
  • Assignments
  • Webinars
  • Discussions

You can access the course from a desktop, laptop, tablet and mobile devices with access to the internet. The EMERITUS Learning Platform is cloud-based and is synchronized across all devices. If you have an iPhone or an Android device, you can also download the Canvas App and access the course. When you download the application, you will be asked to enter a URL. Please enter: student.emeritus.org followed by your login ID and password.

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