This Data Science and Application program equips students with knowledge in data analytics, statistics, and the skills needed as a data analyst or data scientist.
Since 2003, Metro College of Technology has trained and produced thousands of data analysts and data scientists in Canada through this Data Science and Application program.
This Data Science and Application program equips students with knowledge in data analytics, statistics, and the skills needed as a data analyst or data scientist. In essence, they will delve into in-depth statistics and learn how to utilize SQL, VBA Programming, SAS, R, and Python for data science and data analysis projects.
The program also covers data mining, advanced statistical modeling, big data analytics, and machine learning and deep learning. Additionally, students will gain expertise in organizing and presenting data analytics insights using Tableau.
The mini- and capstone projects within this data analysis course provide an excellent opportunity for students to apply their statistical knowledge and data analysis skills to solve practical problems. We are proud of our instructors. They have a strong educational background, successful work experience in this field, and excellent teaching expertise.
Upon successful completion of this data analysis course, students will be awarded an advanced diploma, making them competent candidates for various data science and data analysis positions such as data scientist, data analyst, and data engineer.
Our instructors are not only qualified professionals but also industry-specific experts. Every one of our programs is designed with input from industry leaders to prepare you with the industry know-how.
This course will focus on job-oriented technical skills. Learning modelling techniques and how to populate these data models, using Extract, Transform and Load (ELT) Technologies.
In this course, you will dive into the basics of machine learning using Python, a well-known programming language. Get introduced to data exploration and discover the various machine learning approaches like supervised and unsupervised learning, regression, classifications, and more.
Data analysts work with technical resources to identify a stakeholder’s best approach using the right databases and tools. Working to make sense of large, unsorted amounts of data, analysts establish a workflow while working with the client to automate their processes.
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This course offers practical implementation of Big Data on various frameworks, such as Hadoop, Hive, Pig, Spark, Scala, etc.
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