Certificate in Machine Learning

Program Overview | Available Sessions | Program Policies

Winter 2019

This will also add the following products to your cart:

  • ML1000 Machine Learning in Business Context
  • ML1010 Applied Machine Learning and Lifecycle
  • ML1020 Machine Learning at Scale
  • ML1030 Machine Learning Capstone

$6,799.00 (CAD)

In the current job market, it’s not enough to be a Python wizard or statistical genius. Top employers are looking for machine learning specialists who understand the business and ethical impact of their work. The Certificate in Machine Learning was created in collaboration with industry leaders, including major banks, ensuring that you graduate with the exact skills and real-world experience that will land you the job you want.

You’ll work on one main machine learning project from start to finish, giving you the chance to build upon your technical skill while gaining a holistic understanding of machine learning as it relates to current business applications. You’ll learn key skills that will allow you to:

  • Build a business case to support the implementation of machine learning solutions in various industries
  • Identify and assess the viability of different machine learning models using data, and explain your recommendations clearly to an employer
  • Use project management principles to plan and execute a machine learning solution
  • Use Python (and other languages) to create, implement and test machine learning algorithms in real-world scenarios

ML1000 Machine Learning in Business Context

You will learn the building blocks and tools that will empower you to take raw data sets and extract valuable insights and data visualizations that bring the data to life. You will be introduced to R programming and learn to manipulate data using various R libraries while working in RStudio and Weka. You will also be introduced to common algorithms and techniques for analyzing data and be introduced to the concepts, practices and tools that are used to implement machine learning. The course is designed to be practical and allow students to quickly apply their new skills to real world problems, with real datasets and using the CRISP-DM methodology.
Schedule:
From 25-Jan-2019 to 22-Mar-2019
Onsite January 25, 26, 27; Online; Onsite March 22.
# of Classes:
4
# of Hours:
36.00

ML1010 Applied Machine Learning and Lifecycle

You will cover the lifecycle of machine learning working with Python and R, including processing unstructured data, feature engineering, dimensionality reduction, model selection and optimization, performance evaluation, and model improvement. You will cover advanced algorithms for complex problems that require specialized methods. You will gain hands-on experience with advanced algorithms such as ensemble methods, sequence models, association rule mining, and neural networks. You will construct models using data from a variety of application domains. Time will also be allotted throughout the course to expose students to various ethical and public policy considerations of their work.
* successful completion of ML1000 is required to begin ML1010.
Schedule:
From 23-Mar-2019 to 24-May-2019
Onsite March 23, 24; Online; Onsite May 24.
# of Classes:
3
# of Hours:
36.00

ML1020 Machine Learning at Scale

Having an understanding of the concepts of machine learning, you will examine and apply the fundamentals of working with extremely large data sets. First, you will parallelize and perform MapReduce operations using Hadoop and Spark. Second, you will take a look at the fundamentals of deep learning and working with TensorFlow/CNTK and Keras. You will focus on image and voice data and build deep neural network models. At the end of this module, you should be ready to take on a large-scale real-world project challenge.
* successful completion of ML1010 is required to begin ML1020.
Schedule:
From 25-May-2019 to 19-Jul-2019
Onsite May 25, 26; Online; Onsite July 19.
# of Classes:
3
# of Hours:
36.00

ML1030 Machine Learning Capstone

In the machine learning capstone course, students address a business problem facing an organization by applying analytics models, methodologies, and tools learned in the program. The course will allow students to work on an end-to-end machine learning solution from problem formulation all the way to its deployment. As a result, students will create a data product that can be used to show their skill set to potential employers. The course will also provide an opportunity for students to work closely with business stakeholders, provides a networking opportunity, and exposes them to a real business setting.
* successful completion of ML1020 is required to begin ML1030.
Schedule:
From 20-Jul-2019 to 15-Sep-2019
Onsite July 20, 21; Online; Onsite September 14, 15.
# of Classes:
4
# of Hours:
36.00

Confidentiality and Financial Security

Given the experiential and practical nature of the courses and the application of Ontario’s Freedom of Information and Protection of Privacy Act (FIPPA) to York University, The School of Continuing Studies works to ensure that instructors and participants acknowledge and respect the privacy and confidentiality of personal information that may be presented in the context of instruction. Instructors will limit the amount of personal information that is collected, used or disclosed in their sessions, and will ensure that all identifying personal information (including proper name, address, etc.) is omitted from all written documents in order to protect personal privacy and confidentiality. Instructors should not bring or share personal or other confidential files or records with the class or allow students to do so.

We are committed to protecting your privacy and your financial security, and we do this in several ways:

  • Your credit card information is never received or stored by our system. Only your financial institution has access to your credit card information.
  • Your Student Portal is password-protected. To access any personal and academic information, you must enter your username and portal password.

York University Privacy Policy

How to Register

All registrations are processed on a first-come, first-served basis. Registration is not guaranteed and programs can reach its maximum enrolment capacity, so early registration is recommended.

The School of Continuing Studies reserves the right to alter fees, other charges, instructors and course dates/locations.

Online – Visit our website at continue.yorku.ca to register in any course or program offered by the School of Continuing Studies.

Fees

The School of Continuing Studies allows students in this program to pay in multiple installments. You must pay the initial payment as stated below and with the remainder paid upon program start.

The instalment plan comes with a one-time, non-refundable administrative fee of $125 due at the time of registration. The following are the details of the instalment plan policy according to the program you have registered for:

  • Customized payment plans are available to those being partially or fully reimbursed by their employer. For further information please contact the Registration and Student Records Coordinator at 416-736-5616.
  • A student that fails to make instalment payments as required will not be permitted to continue in the program.

Mailing Address and Changes in Personal Status

All correspondence, including your registration confirmation, grade report and refund cheque, will be sent to the email address provided at the time of registration.
To maintain accurate student records, notification of any changes to your name, address and contact information are required. To update your personal information:

  • Log in to the Student Portal with your student ID and password and update your personal information OR
  • go online to Contact Us and email all changesOR
  • submit a written request to the Registration and Student Records Coordinator at regscs@yorku.ca

All name-change requests must be accompanied by official documentation justifying such a change.

We will not accept telephone requests to change a name or address.

Education and Amount Certificates (Income Tax Receipts) (T2202A)

Income Tax receipts will be available online in February of the following year. Please refer to the income tax guide for allowable deductions.

Session Transfer

Students must contact the Program Manager for permission to transfer to another session.

Transfer requests are only granted for documented medical reasons. Please contact the program manager for information on the required documentation.

Withdrawal from the Program

Students registered in a part-time program that is less than 1 year in length may withdraw from the program. However, they are strongly advised to consult with the Program Manager before a final decision is made. A full refund is granted only when the School of Continuing Studies cancels a program. Refunds will be issued using the initial method of payment or by cheque, if original payment was made by money order. Withdrawal requests must be submitted on the official School of Continuing Studies Withdrawal Request Form to the School of Continuing Studies and subject to the terms listed below.

 

  • If you withdraw 7 calendar days prior to the start of the program, you will receive a 75% refund of program tuition instalment and no academic penalty.
  • If you withdraw between 6 calendar days prior to the start of the program to 7 calendar days after the start of the program, you will receive a 50% refund of program tuition instalment and a $50 administrative fee and no academic penalty.
  • No refunds will be issued after the first 7 days of the program.

Refunds will be issued using the initial method of payment or by cheque, if original payment was made by money order.

Notification of change or cancellation of classes

When necessary, the School of Continuing Studies may alter, postpone or cancel classes. In these instances, students will be notified by email, based on the information provided at the time of registration.
Cancellations or changes will also be posted on the School of Continuing Studies Twitter account.

Cancellation of courses/programs – Fee Refunds

The School of Continuing Studies reserves the right to withdraw or cancel programs/courses. Should a course or program be withdrawn or cancelled, the School will issue a full refund of fees paid.

University Policy on Student Conduct

Students and instructors are expected to maintain a professional relationship characterized by courtesy, collegiality and mutual respect, and to refrain from actions that would be disruptive to such a relationship;

It is the responsibility of the instructor to maintain an appropriate academic atmosphere in the classroom, and the responsibility of the student to cooperate in that endeavour; and,

The instructor is the best person to decide, in first instance, whether such an atmosphere is present in the class, and may, at their discretion, take steps that they feel are appropriate to resolve an issue or dispute.

In any case where a student feels that this policy has been violated, they are urged to notify the instructor of the course/program as soon as possible. Students may be asked to provide a detailed written description of their complaint to the instructor. The instructor may take measures they feel are appropriate to resolve the issue and/or may forward the complaint to the Program Manager for review. Please refer to the full policy document on the York University website at: http://www.yorku.ca/scdr/

Grading

Students registered in certificate programs will be evaluated using the following categories of achievement:

Grade Grade Point Per Cent Range Description
A+ 9 90-100 Exceptional
A 8 80-89 Excellent
B+ 7 75-79 Very Good
B 6 70-74 Good
C+ 5 65-69 Competent
C 4 60-64 Fairly Competent
D+ 3 55-59 Passing
D 2 50-54 Marginally Passing
E 1 (marginally below 50%) Marginally Failing
F 0 (below 50%) Failing


Note: 
all of the above-noted grades are used to calculate averages and credits.

Definitions of Grading Descriptions

A+ Exceptional. Thorough knowledge of concepts and/or techniques and exceptional skill or great originality in the use of those concepts/techniques in satisfying the requirements of an assignment or course.

A Excellent. Thorough knowledge of concepts and/or techniques together with a high degree of skill and/or some elements of originality in satisfying the requirements of an assignment or course.

B+ Very Good. Thorough knowledge of concepts and/or techniques together with a fairly high degree of skill in the use of those concepts/techniques in satisfying the requirements of an assignment or course.

B Good. Good level of knowledge of concepts and/or techniques together with considerable skill in using them to satisfy the requirements of an assignment or course.

C+ Competent. Acceptable level of knowledge of concepts and/or techniques together with considerable skill in using them to satisfy the requirements of an assignment or course.

C Fairly Competent. Acceptable level of knowledge of concepts and/or techniques together with some skill in using them to satisfy the requirements of an assignment or course.

D+ Passing. Slightly better than minimal knowledge of required concepts and/or techniques together with some ability to use them in satisfying the requirements of an assignment or course.

D Barely Passing. Minimum knowledge of concepts and/or techniques needed to satisfy the requirements of an assignment or course.

E Marginally Failing.

F Failing.

Students must achieve a passing grade in each course as they progress through the program. In the event that a student does not receive a passing grade, they must retake that course in the following session—and subsequently pass that course—before proceeding to successive courses.

Grade Appeal and Reappraisal and Petitions

Students may, with sufficient grounds, request a reappraisal of any “tangible” work required for a course/program. Tangible work may include written, graphic, digitized, modelled, video recording or audio recording formats. Students seeking a grade reappraisal must complete and submit the attached form, along with the original work and instructions for the assignment, to the Program Manager within 2 weeks of the date of issue of the letter of grade.
Students and instructors will be informed in writing of the reappraisal result and the reappraiser’s comments. The School of Continuing Studies will ensure the anonymity of both the student and the reappraiser.

Download a Grade Reappraisal form

Financial Petitions

You may submit a financial petition if you experience a serious documented medical illness or a death of an immediate family member that causes you to drop courses. Financial petitions may be granted at the discretion of the University, and will be considered for a period of one year after the occurrence of the illness or death.

The Financial Petition form is located here: http://sfs.yorku.ca/refunds/petitions/

Please complete the form and return it via email cpehelp@yorku.ca or via fax at 416-650-8042.

This will also add the following products to your cart:

  • ML1000 Machine Learning in Business Context
  • ML1010 Applied Machine Learning and Lifecycle
  • ML1020 Machine Learning at Scale
  • ML1030 Machine Learning Capstone

$6,799.00 (CAD)