Overview
Bridge theory and practical experience to transform big data into actionable insights
When you’re ready for an experienced-level of big data analytics, open source technologies and cloud computer platforms, our Big Data Programming & Architecture program can help you reach your goals. Expand on your current knowledge and stay ahead in this rapidly changing field.
- Experience-level data science, machine learning and the latest technical/software and cloud applications
- Experience hands-on courses and computer lab training with the latest big data and architecture tools
- Learn online from leading practitioners dedicated to transferring their knowledge to their students
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Program highlights Learn More
- Advanced courses to expand your Big Data Programming and Architecture skills
- Convenient online virtual classroom format
- Earn a certificate or a certificate of professional learning
- Open enrolment program
Big Data Programming & Architecture program features:
- Advanced level content in areas of data science, machine learning and big data technologies and software applications
- Learn from instructors with industry expertise
- Complete a capstone project that provides students with a real-world business problem in order to apply the skills and tools learned in the program
What you'll learn Learn More
- Data Management and Programming
- Cloud computing essentials
- Machine learning for Big Data Analytics
- Data programming, including Scala and Java
Through our Big Data Programming and Architecture program, you’ll learn to:
- Work with open source and scalable document database tools to search and manage large data sets efficiently
- Develop solutions for extracting and analyzing big data sets using various technologies like Scala and Java, real-time analytics tools, such as Kafka and Hbas, NoSQL and more
- Implement cloud computing concepts
- Build IT infrastructure on the cloud
- Propose and refine analytical solutions to business problems
- Collect, analyze, interpret and share data and identify relationships and data
- Work with open source and scalable database tools
- Prepare to pursue designations such as the Certified Cloud Practitioner and Cloud Solutions Architect
Programming tools used:
- Python
- SAS
- R
- Tableau
- PowerBI
- Scala JavaScript
- SQL and NOSQL technologies (e.g. Cassandra)
- MongoDB & Atlas
- Ataccama DQ
- Metadata Manager / Excel
- Hadoop (MapReduce), DataBricks, HDFS, PIG Spark & Kafka, HBase
- AWS, Azure, and GCP cloud technologies
- ELK stack, Elasticsearch, Logstash, and Kiban
Learn more about the Big Data Programming and Architecture program
- Graduates with a degree or diploma in science, computer science, technology, mathematics, business or engineering
- Professionals with prior academic and work experience in data analytics, data science, computer science, information technology, software engineering and other related technology streams
- Employees in finance, insurance, health care, marketing, retail, government, logistics, transportation, information systems, media/entertainment sectors or other sectors that utilize predictive analytics and artificial intelligence (AI)
- Individuals seeking a new career path in big data analytics & architecture, data engineering, cloud technology and web analytics
- Individuals preparing to pursue designations such as Certified Cloud Practitioner or Cloud Solutions Architect
Earning a Big Data Programming & Architecture Certificate or Certificate in Professional Learning could lead to a wide range of careers, including:
- Big Data Architect
- Database Developer
- Business Intelligence Analyst
- Data Scientist
- Data Analyst
- Data Visualization Developer
- Machine Learning Engineer
- Business Analytics Specialist
- Big Data Developer
- Data Scientists
Upon completion of the program, students will:
- Translate a business problem into an analytics problem
- Propose, and refine, analytical solutions to business problems
- Collect, analyze, interpret, and share data
- Identify relationships in data
- Select problem-solving techniques and software tools to test analytical solutions
- Work with open source and scalable document database tools to search and manage large data sets efficiently
- Implement cloud computing concepts
- Build a variety of IT infrastructure on the cloud
- Prepare to pursue designations such as the Certified Cloud Practitioner, and Cloud Solutions Architect
- Demonstrate an awareness of ethical practices and professional standards applicable to the field of data analytics
- Exemplify the skills, attitudes and behaviours required to work and collaborate with people and develop personal management skills
- Employ effective communication practices
Are you a current McMaster University undergraduate student?
Explore the ElevateYourSkills option to learn how you can earn a Big Data Programming & Architecture certificate as part of your degree.
- Use your electives to earn a professional certificate or diploma
- Fully online courses that you can fit into your schedule
- Providing you with real-life career skills and experience before you graduate
Check out our latest Technology and Data Program Preview webinar to learn more about our Big Data Programming & Architecture program
What our recent graduates say
The flexibility of the course helped me a lot to balance my work.
The flexibility of the course helped me a lot to balance my work. Our field in data is continuously changing. I found that sweet balance in terms of the focus of the course. It’s a life cycle of how the data is coming in all the way to make it a service or a product. The course gives you that 360 spectrum.
Zaki
Big Data graduate
The flexibility of the course helped me a lot to balance my work.
The flexibility of the course helped me a lot to balance my work. Our field in data is continuously changing. I found that sweet balance in terms of the focus of the course. It’s a life cycle of how the data is coming in all the way to make it a service or a product. The course gives you that 360 spectrum.
Zaki
Big Data graduate
Other programs you may be interested in
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Certificates in Big Data Programming and Architecture
Certificate in Big Data Programming and Architecture
Pursue your Certificate in Big Data Programming and Architecture with McMaster Continuing Education
Explore the requirements below and register today!
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Certificate in Big Data Programming and Architecture Learn More
Earn the Certificate in Big Data Programming & Architecture by completing five elective courses from the courses listed.
Certificate in Big Data Programming and Architecture Requirements
Academic credit: 15 units
Students should possess a minimum of intermediate level prior education or work experience in the field of data analytics and/or statistics.
Bring Your Own Device (BYOD) policy
The Big Data Programming & Architecture program follows a Bring Your Own Device (BYOD) policy. Prior to enrolling it is recommended to review course outlines for laptop and desktop requirements as courses may need a minimum level of technology specification.
Microsoft Excel
Big Data Programming & Architecture requires varying degrees of proficiency in Microsoft Excel. Basic knowledge of Microsoft Excel is recommended to be successful in the courses. Excel course modules are available through LinkedIn Learning, free of charge, to all active McMaster University students. Please visit LinkedIn Learning for more information.
Do you need additional training?
Additional training is available for Python programming, SQL, and PowerBI through our partner Ed2Go. Please visit our Professional Development page for more information.
Courses (complete any 5)
Certificate of Professional Learning in Big Data Programming and Architecture
Pursue your Certificate of Professional Learning in Big Data Programming and Architecture with McMaster Continuing Education
Explore the requirements below and register today!
Information Box Group
Certificate of Professional Learning in Big Data Programming & Architecture Learn More
Earn the Certificate of Professional Learning in Big Data Programming & Architecture by completing three elective courses from the courses listed.
Certificate of Professional Learning in Big Data Programming and Architecture Requirements
Academic credit: 9 units
Students should possess a minimum of intermediate level prior education or work experience in the field of data analytics and/or statistics.
Bring Your Own Device (BYOD) policy
The Big Data Programming & Architecture program follows a Bring Your Own Device (BYOD) policy. Prior to enrolling it is recommended to review course outlines for laptop and desktop requirements as courses may need a minimum level of technology specification.
Microsoft Excel
Big Data Programming & Architecture requires varying degrees of proficiency in Microsoft Excel. Basic knowledge of Microsoft Excel is recommended to be successful in the courses. Excel course modules are available through LinkedIn Learning, free of charge, to all active McMaster University students. Please visit LinkedIn Learning for more information.
Do you need additional training?
Additional training is available for Python programming, SQL, and PowerBI through our partner Ed2Go. Please visit our Professional Development page for more information.
Courses (complete any 3)
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- Big Data Programming & Architecture Program
Big Data Programming & Architecture Schedule
Big Data Programming and Architecture course schedules to help you plan your academic year.
Registration: Fall and Winter terms open in mid-July and Spring term opens in mid-March.
Program Requirements: Review certificate or diploma tab.
Time Zone: Courses run in the Eastern Time (ET) Zone.
Course Fees: A McMaster Part Time Student fee is included in the cost of academic credit courses. There is no tax on courses unless indicated at the bottom of the schedule chart.
Additional Fees: New students pay a one-time, non-refundable $39 activation fee for their first academic-credit course. Not every program or course requires textbooks. Learn more about textbooks.
Learning Formats: Visit Learning Formats to determine the best format for you.
Course Name (Course Date) | Cost | Units | Fall 2024 | Winter 2025 | Spring/Summer 2025 |
---|---|---|---|---|---|
Data Management (DAT 202) | $1,109.28 | 3.0 | — | Wed, Jan 22 - Apr 9 7:00 p.m. - 10:00 p.m. Format: Virtual Classroom | — |
TBD | 3.0 | — | — | Wed, May 7 - Jul 23 7:00 p.m. - 10:00 p.m. Format: Virtual Classroom | |
Machine Learning for Big Data Analytics (DAT 301) | $1,109.28 | 3.0 | — | Sat, Jan 18 - Apr 12 1:00 p.m. - 4:00 p.m. Format: Virtual Classroom | — |
TBD | 3.0 | — | — | Tue, May 6 - Jul 29 7:00 p.m. - 10:00 p.m. Format: Virtual Classroom | |
Data Programming I (DAT 302) | - | - | Currently Not Available | ||
Data Programming II (DAT 303) | TBD | 3.0 | — | — | Sun, May 11 - Aug 17 9:00 a.m. - 12:00 p.m. Format: Virtual Classroom |
Essentials of Cloud Computing (DAT 304) | $1,109.28 | 3.0 | — | Mon, Jan 13 - Apr 7 7:00 p.m. - 10:00 p.m. Format: Virtual Classroom | — |
Capstone Project - Big Data Programming and Architecture (DAT 305) | $1,109.28 | 3.0 | — | Wed, Jan 22 - Apr 9 7:00 p.m. - 10:00 p.m. Format: Virtual Classroom | — |
The schedule table is subject to change. Please visit the course pages to browse classes currently available for registration and the latest cost information.
Admission Requirements
Admission Requirements
This program is open enrolment, which means there is no formal application or admission procedure. To enrol in a course, simply register online. Our courses can be taken as part of a program or individually.
To enrol in McMaster Continuing Education programs, you must:
- Have an Ontario Secondary School Diploma or equivalent
- Be a mature student as defined in the Undergraduate Calendar of McMaster University or
- Be deemed an exceptional case
To ensure you are successful in your online courses, you are required to have knowledge and skills with general computer applications, such as keyboarding, file management, video conferencing and word processing.
Language Requirements
If your first language is not English, you must meet the University’s English language proficiency requirements. Completion of TOEFL exam with a minimum acceptable score of 20 on each of the four components (reading, writing, speaking and listening), valid for 2 years.
Expandable List
- Visit continuing.mcmaster.ca/programs to find your program of choice
- Click on each tab on the program page to learn about credential options and requirements, schedule and fees, and a list of all courses in the program
- Select a course and then select an available offering, noting important information such as cost, delivery format, and start/end dates; then click ‘add to cart’
- Once you have added your courses, click the shopping cart icon at the top right-hand corner of the page (bottom of the browser screen on mobile)
- Review your cart and, once you’re ready to proceed with enrolment, click ‘proceed to checkout’
- As the next step, you will be redirected to Mosaic – McMaster’s Administrative Information and Enrolment system
- Once you are in Mosaic, select ‘new to McMaster’ or log in with your existing MacID and password (if applicable)
- Complete all required fields and select a program of study when prompted (i.e., a specific program or open studies for standalone courses)
- Finally, payment is required in full to secure a spot in your course(s)
A payment receipt email will be issued to you immediately after registering, and a course confirmation email will be sent to you overnight. Within approximately 24 hours of registering, you will also receive an important email containing credentials used to activate your MacID, which you must do before you can access courses in Avenue to Learn. Please review our Getting Started page to learn more about the next steps for beginning your studies after registration, and our Help Centre for our Refund Policy and other frequently asked questions. Please note that on average, each course requires 6-8 hours of study per week, per course (sometimes more) and some courses may have listed prerequisites. Please plan your schedule accordingly. Most students take 1-2 courses per term across a few different terms and a full-time equivalent course load is typically 3-4 courses per term.
For more information and a walkthrough on how to register, please check out this video.
- Payment must be made in full at the time of enrolment
- Online credit card or debit payments are preferred
- Accepted credit cards: Visa, MasterCard and American Express
- Accepted debit cards: Visa Debit and Debit Mastercard
- Google Pay is available for faster checkout
- Payments can be made from a Canadian Financial Institution and can take 2 to 4 business days to arrive in your McMaster student account. Once payment has arrived, you can register for your course. Please note that if the amount of the course fees owing is more than what was transferred to your student account, you will be dropped from the course.
- Problem processing your payment? Please reach out to your credit card company if your payment was declined. Otherwise, wait two hours before attempting your registration again.
Ready to get started?
Visit the Schedule tab to select your course and proceed with the registration steps.