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ONLINE AND PART-TIME COURSE REGISTRATION

Business Analysis & Analytics   

  • Applying Statistics [CSCG1000]
  • Fee: $410.67
    Delivery: Online - OntarioLearn
    Course Code: CSCG1000
    Dates: 1/13/2026 - 4/21/2026
    ONLINE REGISTRATION FOR THIS SECTION IS CLOSED.
    To inquire about this course contact lifelonglearning@sl.on.ca.

    This course introduces statistical techniques to evaluate quality and analyze processes and products. The course covers fundamentals of statistics, descriptive statistics, probability, binomial probability distribution, normal probability distribution, inferential statistics, and linear regression analysis. Students will be able to practice mathematical formulae as they relate to statistical methods as well as apply Excel to solve statistical problems. The course will develop skills of statistical analysis and decision-making. No Textbook Required.

    Software Required: MS Excel


 

  • Data Analysis Tools for Analytics [CSAL224]
  • Fee: $410.67
    Delivery: Online - OntarioLearn
    Course Code: CSAL224
    Dates: 1/13/2026 - 4/21/2026
    ONLINE REGISTRATION FOR THIS SECTION IS CLOSED.
    To inquire about this course contact lifelonglearning@sl.on.ca.

    Students are introduced to different scripting language tools such as SQL, NOSQL, Apache, Java and Python that support data analysis on large volumes of data. They also analyze the strengths and limitations of current tools used today. Students review and recommend which tools best support data analysis, data quality, problem solving, analysis, analytics and business decision-making for different functions and industries.

    NOTE: This course has mandatory chats. No Textbook Required


 

  • Data Collection and Data Management [CSAL225]
  • Fee: $410.67
    Delivery:
    Course Code: CSAL225
    Dates: 1/13/2026 - 4/21/2026
    ONLINE REGISTRATION FOR THIS SECTION IS CLOSED.
    To inquire about this course contact lifelonglearning@sl.on.ca.

    Students are introduced to data sources, informatics, data models, data management and data ownership; all key components to the data-driven organization. They analyze the common practices, prioritization approaches, system workload and security challenges for systems that support high data volumes and analytics. Students assess the individual, legal and society impacts of collecting data, including social media data. They also assess the historic problems with data collection and data management and how the current tools are used to address these problems.

    NOTE: This course has mandatory chats. No Textbook Required


 

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