Program Overview

Big Data Programming and Architecture Program

The Big Data Programming and Architecture program is designed to help individuals bridge the gap between theoretical knowledge and practical experience in big data analytics, open-source technologies, and cloud computing platforms. This program is ideal for those seeking to expand their current knowledge and stay ahead in the rapidly changing field of big data.

Program Overview

The program is structured to provide advanced-level content in areas of data science, machine learning, and big data technologies and software applications. Students will learn from instructors with industry expertise and complete a capstone project that provides a real-world business problem to apply the skills and tools learned in the program.

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 to apply the skills and tools learned in the program

What You'll Learn

• Data Management and Programming
• Cloud computing essentials
• Machine learning for Big Data Analytics
• Data programming, including Scala and Java
• 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
• 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
• 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

Program Schedule

The program is offered in a virtual classroom format, with approximately 7-9 hours of study per week, per course. The certificate program can be completed in 12+ months.

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.

Who Should Take This 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, healthcare, 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

Career Opportunities

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

Academic Learning Outcomes

Upon completion of the program, students will:

1. Translate a business problem into an analytics problem
2. Propose, and refine, analytical solutions to business problems
3. Collect, analyze, interpret, and share data
4. Identify relationships in data
5. Select problem-solving techniques and software tools to test analytical solutions
6. Work with open source and scalable document database tools to search and manage large data sets efficiently
7. Implement cloud computing concepts
8. Build a variety of IT infrastructure on the cloud
9. Prepare to pursue designations such as the Certified Cloud Practitioner, and Cloud Solutions Architect
10. Demonstrate an awareness of ethical practices and professional standards applicable to the field of data analytics
11. Exemplify the skills, attitudes, and behaviours required to work and collaborate with people and develop personal management skills
12. Employ effective communication practices

Certificate in Big Data Programming and Architecture

Earn the Certificate in Big Data Programming & Architecture by completing five elective courses from the courses listed.

Certificate 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
• Microsoft Excel: Basic knowledge of Microsoft Excel is recommended to be successful in the courses.

Certificate of Professional Learning in Big Data Programming and Architecture

Earn the Certificate of Professional Learning in Big Data Programming & Architecture by completing three elective courses from the courses listed.

Certificate of Professional Learning 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
• Microsoft Excel: Basic knowledge of Microsoft Excel is recommended to be successful in the courses.

Courses

• DAT 202: Data Management
• DAT 301: Machine Learning for Big Data Analytics
• DAT 302: Data Programming I
• DAT 303: Data Programming II
• DAT 304: Essentials of Cloud Computing
• DAT 305: Capstone Project - Big Data Programming and Architecture

Registration

Visit the program page to find your program of choice, click on each tab 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.