Data Analytics with AI (Program)

Our data analytics program will help you acquire or refresh the software skills and statistical knowledge needed to assist you on taking more data-driven decisions to improve business performance.

Courses are delivered online and in real time. The program is comprised of seven courses, which could be taken in any order, based on availability:

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1. Applied Data Analytics with Python: You will learn the data analytics process to turn data into actionable insights to improve business performance. Principles of data preparation, exploration modeling and deployment using statistics and machine learning methods are discussed. Alternatively, this course could be offered using Excel, R, PowerBI or SAS.

2. Machine Learning Models with Python: You will learn the use cases of the mostly used machine learning algorithms to handle real world, messy data, including support vector machines, Naïve Bayes and reduction techniques. Alternatively, this course could be offered using the R language.

3. Data Visualization with Tableau: You will learn the fundamental principles for creating meaningful displays of quantitative and qualitative data to facilitate decision-making. Alternatively, it could be offered using PowerBI.

4. Microsoft SQL and MySQL for Data Analytics: You will learn the relevant aspects of SQL when it comes to retrieving data, including advanced techniques like windows functions, unions, joins and subqueries.

5. Big Data Tools and Techniques: You will learn the principles of working with big data, including deploying virtual machines, working with non-SQL databases such as Cassandra and managing multiple clusters using Databricks.

6. Spreadsheet modeling using Excel: You will learn fundamental statistic principles and how to properly design spreadsheets to perform advanced analytics including simulation, optimization, regression, time-series and what-if analysis.

7. Statistical analysis with SAS: You will learn how to create SAS programs to analyze data sets from various sources, including Excel and flat files, and to review statistical concepts, such as descriptive statistics, statistical data visualization and inferential statistics, including multiple linear regression and logistic regression. Alternatively, this course could be offered in Excel, R or Python

Subsidized tuition fee:

Not offered this semester.

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Last Modified: January 30, 2023